Loading...
Challenges in microbial ecology: Building predictive understanding of community function and dynamics
Widder, S Allen, RJ Pfeiffer, T Curtis, TP Wiuf, C Sloan, WT Cordero, OX Brown, SP Momeni, B Shou, W
Widder, S
Allen, RJ
Pfeiffer, T
Curtis, TP
Wiuf, C
Sloan, WT
Cordero, OX
Brown, SP
Momeni, B
Shou, W
Citations
Altmetric:
Genre
Review
Journal
Journal
Date
2016-11-01
Advisor
Committee member
Group
Department
Permanent link to this record
Collections
Research Projects
Organizational Units
Journal Issue
DOI
10.1038/ismej.2016.45
Abstract
© 2016 International Society for Microbial Ecology All rights reserved. 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.
Description
Citation
Citation to related work
Springer Science and Business Media LLC
Has part
ISME Journal
ADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu