Spatially explicit, individual‐based, behavioural models of the annual cycle of two migratory goose populations

1. Behaviour‐based models of animal population dynamics provide ecologists with a powerful tool for predicting the response of such populations to both natural and human‐induced environmental changes. 2. We developed this approach by addressing two outstanding issues in the application of such models: the need to adopt a large‐scale spatially explicit approach, and the need to consider the year‐round dynamics of animal populations. 3. Spatially explicit, year‐round, behaviour‐based models of two populations of arctic‐breeding geese, the Svalbard population of the barnacle gooseBranta leucopsisand the dark‐bellied race of the brent gooseBranta bernicla, were developed. Both populations have been the subject of serious conservation concern and are currently a source of increasing conflict with agricultural interests. 4. There was generally good agreement between empirically derived and model‐generated density‐dependent functions, and of seasonal patterns of the distribution and movement of populations within and between sites, and of energy reserve levels within a population. 5. Sensitivity analyses, however, highlighted the importance of accurate parameter estimation with respect to the predictions of such models, and the potential flaws in the predictions of existing models that have not adopted a spatially explicit approach when dealing with wide‐ranging migratory populations. 6. The effect of the removal of a given area of habitat on both populations was predicted to vary depending upon the spatial configuration of the change. This further emphasizes the need for a spatially explicit approach. 7. Both barnacle goose and brent goose populations were predicted to decline following habitat loss in their winter or spring‐staging sites. Simulations suggested that barnacle geese might be less vulnerable to winter habitat loss than brent geese. This reflected the relative strengths of the density‐dependence of productivity and winter mortality in the two models and provided a clear illustration of the need for a year‐round approach to animal population dynamics. 8. We believe that these models, and this approach to understanding the population dynamics of long‐distance migrants, will be beneficial in attempting to answer the increasingly urgent and frequent requests to predict the response of such populations to environmental change.