Challenges in microbial ecology: building predictive understanding of community function and dynamics

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in…

• IN
  Isaac Newton Institute for Mathematical Sciences
• DF
  Directorate for Biological Sciences
• MR
  Medical Research Council

  Awards: MR/M50161X/1, MR/L015080/1
• EA
  Engineering and Physical Sciences Research Council

  Awards: EP/K032208/1, EP/H009604/1, EP/K038885/1
• BA
  Biotechnology and Biological Sciences Research Council

  Award: BB/K003240/2
• DO
  Division of Mathematical Sciences
• AR
  Army Research Office

  Awards: W911NF-14-1, W911NF