Predicting ecosystem emergent properties at multiple scales

Abstract

Biological phenomena at the microbial community level encode information about the subpopulation of cells and taxa at a specific time in the succession and biogeochemical evolution of that assemblage. To capture and understand the entire population for a community at a temporal resolution at which biogeochemical processes influence geological climate dynamics, requires large-scale computational simulations of their formation and evolution. The interactions between components of biology, geochemistry and physical processes within an ecosystem are inherently non-linear, with complex feedback mechanisms. However, this complexity does not preclude quantification of the dynamics that govern the relationships. As such, if we understand the component dynamics at a given scale then prediction of their influences will be feasible, allowing for appropriate simulation of their response to shifts in system properties. While theorizing and experimentation are the most appropriate means of elucidating biological truth in ecological dynamics; simulation, especially for microbial communities, represents a new frontier for designing in silico experiments to test fundamental hypotheses. These can, by definition then be tested through observation, experimental manipulation and theory.