MIGRAZE – Modelling Wildebeest Migration Patterns in the Serengeti-Masai Mara Ecosystem

Understanding the dynamics of migratory systems under global change is essential for effective land use and conservation planning. MIGRAZE is an individual-based ecological model designed to simulate the interactions between ungulate migration and food availability and land use in semi-arid regions. Here, the focus is on wildebeest. The model reflects the Serengeti–Masai Mara ecosystem, where roughly 1.3 million wildebeest migrate annually in response to grass biomass and nitrogen gradients. During the wet season, they feed on the nutrient-rich grasses in the southern Serengeti, before migrating to the wetter Masai Mara as the dry season begins. MIGRAZE integrates this behaviour by simulating movement of super-individuals using the stochastic movement simulator to make the step selection. The direction of the movement is chosen based on land cover type, grass biomass and grass nutrient content in their perceptual range. Vegetation dynamics incorporate rainfall patterns, the accumulation of dry matter and consumption by animals to simulate green grass biomass during the rainy season. We modelled the wildebeest migration in the Serengeti-Masai Mara ecosystem for two decades from 1999 to 2019. The study was validated using tracking data from 67 individuals over the same time period. In order to better identify the mechanisms underlying the large-scale movement patterns we tested two behavioural components. First, we provided the super-individuals with knowledge of the full landscape, which resulted in more directed movements toward their seasonal ranges. Second, we incorporated past environmental conditions by adding the normalized difference vegetation index (NDVI) as memory. This generated stronger movement toward the Masai Mara in the dry season but hindered return migration to the southern Serengeti, as NDVI does not capture grass quality. Overall, our results suggest that broad migratory destinations are shaped by memory and knowledge, whereas immediate movement decisions and the timing and arrival depend on current environmental conditions. This knowledge is of crucial importance when modelling future scenarios, and will assist in anticipating how wildebeest movements might respond to increasing anthropogenic pressures, such as climate and land use change. This, in turn, can inform conservation planning.