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

Isaac Newton Institute Fellows

Research output: Contribution to journalReview articlepeer-review


The importance of microbial communities 1 (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 community 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 important insights into MC function and structure. We also highlight key research questions which still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
Original languageEnglish
Pages (from-to)2557-2568
Number of pages12
JournalThe ISME Journal: Multidisciplinary Journal of Microbial Ecology
Early online date29 Mar 2016
Publication statusPublished - 1 Nov 2016


Dive into the research topics of 'Challenges in microbial ecology: Building predictive understanding of community function and dynamics'. Together they form a unique fingerprint.

Cite this