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Challenges in microbial ecology: building predictive understanding of community function and dynamics
Type of publication
Peer-reviewed
Publikationsform
Review article (peer-reviewed)
Author
Widder S, Johnson David R,
Project
Metabolic specialization and the causes of diversity in microbial ecosystems
Show all
Review article (peer-reviewed)
Journal
ISME Journal
Page(s)
2557 - 2568
Title of proceedings
ISME Journal
Open Access
URL
https://www.nature.com/articles/ismej201645
Type of Open Access
Repository (Green Open Access)
Abstract
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 important insights into MC function and structure. We also highlight key research questions that 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.
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