Predicting impacts of food competition, climate and disturbance on a long-distance migratory herbivore

Climate change is driving worldwide shifts in the distribution of biodiversity, and fundamental changes to global avian migrations. Some arctic‐nesting species may shorten their migration distance as warmer temperatures allow them to winter closer to their high‐latitude breeding grounds. However, such decisions are not without risks, since this intensifies pressure on resources when they are used for greater periods of time. In this study, we used an individual‐based model to predict how future changes in food abundance, winter ice coverage, and human disturbance could impact an Arctic/sub‐Arctic breeding goose species, black brant (Branta bernicla nigricans, Lawrence 1846), and their primary food source, common eelgrass (Zostera marina L.), at the Izembek Lagoon complex in southwest Alaska. Brant use the site during fall and spring migrations, and increasingly, for the duration of winter. The model was validated by comparing predictions to empirical observations of proportion of geese surviving, proportion of geese emigrating, mean duration of stay, mean rate of mass gain/loss, percentage of time spent feeding, number of bird days, peak population numbers, and distribution across the complex. The model predicted that reductions >50% of the current decadal (2007–2015) mean of eelgrass biomass, which have been observed in some years, or increases in the number of brant, could lead to a reduction in the proportion of birds that successfully migrate to their breeding grounds from the site. The model also predicted that access to eelgrass in lagoons other than Izembek was critical for overwinter survival and spring migration of brant, if overall eelgrass biomass was 50% of the decadal mean biomass. Geese were typically predicted to be more vulnerable to environmental change during winter and spring, when eelgrass biomass is lower, and thermoregulatory costs for the geese are higher than in fall. We discuss the consequences of these predictions for goose population trends in the face of natural and human drivers of change