Integrated movement models for individual tracking and species distribution data

Abstract While the quantity, quality, and variety of movement data has increased, methods that jointly allow for population‐ and species‐level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual‐level movement and population‐level distribution data. We show how formal data integration can be used to improve precision of individual and population‐level movement parameters and allow additional population‐level metrics (e.g., connectivity) to be formally quantified. We describe three components needed for an Integrated Movement Model (IMM): a model for individual movement, a model for among‐individual heterogeneity, and a model to quantify changes in species distribution. We outline a general IMM framework and develop and apply a specific stochastic differential equation model to a case study of telemetry and species distribution data for golden eagles in western North American during spring migration. We estimate eagle movements during spring migration from data collected between 2011 and 2019. Individual heterogeneity in migration behaviour was modelled for two subpopulations, individuals that make significant northward migrations and those that remained in the southern Rocky Mountain region through the summer. As is the case with most tracking studies, the sample population of individual telemetered birds is not representative of the population and underrepresents the proportion of long‐distance migrants in the population. The IMM was able to provide a more biological accurate subpopulation structure using joint estimation. In addition, the integrated approach (a) improves accuracy of other estimated movement parameters, (b) allows us to estimate the proportion of migratory and non‐migratory birds in a given location and time, and (c) estimate future spatiotemporal distributions of birds given a wintering location, which provide estimates of seasonal connectivity and migratory routes. We demonstrate how IMMs can be successfully used to address the challenge of estimating accurate population‐level movement parameters. Our approach can be generalized to a broad range of available movement models and data types, allowing us to significantly improve our knowledge of migration ecology across taxonomic groups, and address population and continental level information needs for conservation and management.