Tuesday 30 Nov 2021: Animal movement: memory, ?landscape and population dynamics
Juliana Berbert - Federal University of ABC/Brazil
https://Universityofexeter.zoom.us/j/98128535238?pwd=b1NNR1MwV295VHRWWFh4b1NDTjJoZz09 Meeting ID: 981 2853 5238 Password: 561487 13:30-14:30
Recent studies have suggested that spatial heterogeneity and temporal predictability of resources are factors contributing to define patterns of movement strategies, such as sedentarism (i.e., range residency), migration, and nomadism. Here, we propose that, at the individual level, a dependence on spatial memory is another important parameter for distinguishing among population-level patterns of spatial distribution. For instance, migratory animals would have a long memory of the areas they prefer to revisit, whereas nomadic animals would remember recently visited areas as places to avoid as they search for resources. We develop a computational model in which individuals’ movement decisions are based on the animals’ spatial memory of previously visited areas.Through this approach, we delineate how the interplay between landscape persistence and spatial memory leads to sedentarism, migration, and nomadism. Further, for a mathematical approach, we have also defined a reaction-diffusion-advection equation, in which the reactive part stands for the population growth, the diffusive part for random dispersal of the population, and the advection is due to the individual’s spatial memory of recently depleted patches. Therefore, we propose a mathematical model composed of a coupled nonlinear partial differential equation system with one equation for the movement and population dynamics and another for the individual’s spatial memory density distribution. For population growth, we use either the exponential or logistic growth function. The analytic approach has shown that for the exponential and logistic growth the traveling wave speeds are the same with or without memory dynamics. From the numerical analysis, our model reveals a bias toward the edges of dispersal. We have explored how the population redistribution is affected by different values of the parameters: individual’s memory, growth rate, and carrying capacity. And, combining these parameters results in a redistribution pattern of the population associated with either normal or (smooth) super diffusion. Furthermore, we have defined a region where the influence of memory is stronger than the growth rate.