Opposing Rainfall and Plant Nutritional Gradients Best Explain the Wildebeest Migration in the Serengeti

Abstract

Multiple hypotheses have been proposed to explain the annual migration of the Serengeti wildebeest, but few studies have compared distribution patterns with environmental drivers. We used a rainfall-driven model of grass dynamics and wildebeest movement to generate simulated monthly wildebeest distributions, with wildebeest movement decisions depending on 14 candidate models of adaptive movement in response to resource availability. We used information-theoretic approaches to compare the fits of simulated and observed monthly distribution patterns at two spatial scales over a 3-year period. Models that included the intake rate and nitrogen (N) concentration of green grass and the suppressive effect of tree cover on grass biomass provided the best model fits at both spatial scales tested, suggesting that digestive constraints and protein requirements may play key roles in driving migratory behavior. The emergence of a migration was predicted to be dependent on the ability of the wildebeest to track changes in resource abundance at relatively large scales (>80-100 km). When movement decisions are based solely on local resource availability, the wildebeest fail to migrate across the ecosystem. Our study highlights the potentially key role of strong and countervailing seasonally driven rainfall and fertility gradients--a consistent feature of African savanna ecosystems--as drivers of long-distance seasonal migrations in ungulates.