Stoichiometry in population dynamics and its implications
Yang Kuang (Department of Mathematics and Statistics, Arizona State University)
(November 21, 2005 2:30 PM - 3:30 PM)
Mathematical biologists have built on variants of the Lotka-Volterra equations and in almost all cases have adopted the pure physical science's single-currency (energy) approach to understanding population dynamics. However, biomass production requires more than just energy. It is crucially dependent on the chemical compositions of both the consumer species and food resources. In this review style talk, we explore how depicting organisms as built of more than one thing (for example, C and an important nutrient, such as P) in stoichiometrically explicit models results in qualitatively different and realistic predictions about the resulting dynamics. Stoichiometric models incorporate both food quantity and food quality effects in a single framework, appear to stabilize predator-prey systems while simultaneously producing rich dynamics with alternative domains of attraction and occasionally counterintuitive outcomes, such as coexistence of more than one predator species on a single-prey item and decreased herbivore performance in response to increased light intensity experienced by the autotrophs. We conclude that stoichiometric theory has tremendous potential for both quantitative and qualitative improvements in the predictive power of mathematical population models in the study of both ecological and evolutional dynamics.