Modeling and Theory in Population Biology

Mathematical population biologists study of a wide array of biological phenomena—such as the spread of alleles in a populations, the coexistence of competing species within ecosystems, the branching of phylogenetic trees, the transmission dynamics of infectious diseases, and the demographic history of populations—that are typically studied across distinct biological subfields, including demography, ecology, epidemiology, and population genetics. Although these phenomena are often represented in separate scientific communities, they are united by a core set of mathematical and computational modeling philosophies and approaches. Recent advances in computation and data-gathering technologies have greatly increased our power to test hypotheses about ecological and evolutionary processes and to make detailed inferences about the structure of populations. These advances have facilitated the development of new models for individuals and populations in space and over time, including models that relax some of the core assumptions underlying much of previous theory.

The goal of this workshop is to bring together researchers in population biology who draw on diverse areas, including stochastic processes, mathematical statistics, dynamical systems, combinatorics and, increasingly, computational modeling and simulation, to share the latest mathematical advances and tools across subfields. This exchange of approaches will reveal synergies and spark new research directions.