TY - JOUR
T1 - Challenges in microbial ecology
T2 - Building predictive understanding of community function and dynamics
AU - Widder, Stefanie
AU - Allen, Rosalind J.
AU - Pfeiffer, Thomas
AU - Curtis, Thomas P.
AU - Wiuf, Carsten
AU - Sloan, William T.
AU - Cordero, Otto X.
AU - Brown, Sam P.
AU - Picioreanu, Cristian
AU - More Authors, null
AU - Momeni, Babak
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - http://resolver.tudelft.nl/uuid:0c4efc87-00a8-4518-9a3b-c83e45b66c1f
UR - http://www.scopus.com/inward/record.url?scp=84961904331&partnerID=8YFLogxK
U2 - 10.1038/ismej.2016.45
DO - 10.1038/ismej.2016.45
M3 - Review article
C2 - 27022995
AN - SCOPUS:84961904331
SN - 1751-7362
VL - 10
SP - 2557
EP - 2568
JO - The ISME Journal: multidisciplinary journal of microbial ecology
JF - The ISME Journal: multidisciplinary journal of microbial ecology
IS - 11
ER -