Integrated Population Models

In this chapter, we will introduce integrated population models (IPMs; Fournier and Archibald 1982; Besbeas et al. 2002; Brooks et al. 2004; Schaub and Abadi 2011; Schaub and Kéry 2022; Frost et al. 2023) with a focus on their spatial versions (Borysiewicz et al. 2009; Péron et al. 2010; McCrea et al. 2010; Zhao 2020; Schaub and Kéry 2022; Chapter 20). The idea of data integration in IPMs is to leverage abundance and demographic information by jointly analyzing multiple data sets. A “classic” IPM contains three sub-models, a population sub-model for counts of adult individuals or breeders, a reproduction sub-model for counts of juvenile individuals or offspring, and a survival sub-model (e.g., Cormack-Jolly-Seber/CJS model; Cormack 1964; Jolly 1965; Seber 1965) for capture-recapture data. By analyzing all these data in a joint likelihood, IPMs often achieve improved precision in comparison to the analysis of each data set separately (Schaub and Abadi 2011). Also, IPMs allow for the estimation of latent state variables (e.g., reproduction) without specific data (e.g., counts of juveniles; Besbeas et al. 2002; Tavecchia et al. 2009; Zhao et al. 2019).