Year: 2018
Type: article
Abstract: Summary Through complex interspecies interactions, microbial processes drive nutrient cycling and biogeochemistry. However, we still struggle to predict specifically which organisms, communities and biotic and abiotic processes are determining ecosystem function and how environmental changes will alter their roles and stability. While the tools to create such a predictive microbial ecology capability exist, cross‐disciplinary integration of high‐resolution field measurements, detailed laboratory studies and computation is essential. In this perspective, we emphasize the importance of pursuing a multiscale, systems approach to iteratively link ecological processes measured in the field to testable hypotheses that drive high‐throughput laboratory experimentation. Mechanistic understanding of microbial processes gained in controlled lab systems will lead to the development of theory that can be tested back in the field. Using N 2 O production as an example, we review the current status of field and laboratory research and layout a plausible path to the kind of integration that is needed to enable prediction of how N‐cycling microbial communities will respond to environmental changes. We advocate for the development of realistic and predictive gene regulatory network models for environmental responses that extend from single‐cell resolution to ecosystems, which is essential to understand how microbial communities involved in N 2 O production and consumption will respond to future environmental conditions.
Source: Environmental Microbiology
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
Awards: G1079818582, G1143651532, G1286236842, ABI Innovation: A framework to predictably manipulate a microbial gene regulatory program, G1863003419, Physiologic state modulation by conditional translational complexes, G3083819904, Ocean Acidification: A Systems Biology Approach to Characterize Diatom Response to Ocean Acidification and Climate Change, G419881185, G42916606, G4501827968, G498139845, G7354628648, G969889393
OpenAlex ID: W2887111803