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 bot h natural and human-induced environmental changes. 2. We developed this approach by addressing two outstanding issues in the a pplication of such models: the need to adopt a large-scale spatially explic it approach, and the need to consider the year-round dynamics of animal pop ulations. 3. Spatially explicit, year-round, behaviour-based models of two population s of arctic-breeding geese, the Svalbard population of the barnacle goose B ranta leucopsis and the dark-bellied race of the brent goose Branta bernicl a, were developed. Both populations have been the subject of serious conser vation concern and are currently a source of increasing conflict with agric ultural interests. 4. There was generally good agreement between empiricall y 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 pa rameter 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 pop ulations. 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 chan ge. This further emphasizes the need for a spatially explicit approach. 7. Both barnacle goose and brent goose populations were predicted to declin e following habitat loss in their winter or spring-staging sites. Simulatio ns suggested that barnacle geese might be less vulnerable to winter habitat loss than brent geese. This reflected the relative strengths of the densit y-dependence of productivity and winter mortality in the two models and pro vided 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 pop ulation dynamics of long-distance migrants, will be beneficial in attemptin g to answer the increasingly urgent and frequent requests to predict the re sponse of such populations to environmental change.