About this Research Topic
Resource-limited natural ecosystems, such as grasslands and forests have developed an array of self-regulatory resilient mechanisms to efficiently use their own resources, positively impacting biodiversity, including the soil and plant-associated microbiome, and resource conservation (i.e., N and P). This sustainability relies greatly on the evolution of demand-fitted microbial consortia that provide, in conjunction with the plant community, the necessary chemical resources maintaining ecosystem stability and productivity.
Such self-regulatory mechanisms could be harnessed and used to optimize the ecological resource use efficiency of agro-ecosystems. Considering the tremendous diversity of the terrestrial microbiota and its key role in regulating major nutrient cycles in all ecosystems, relevant functional traits of the soil microbiome in natural ecosystems must first be determined, described in detail and understood. Strategies could then be devised to stimulate these traits in agro-ecosystems to promote agronomic efficiency and ecosystem stability.
This Research Topic of Frontiers of Terrestrial Microbiology will showcase novel approaches used to understand and harness ecological resource use efficiency and biodiversity in natural and agricultural ecosystems. The discussion will include broader ecological reviews on self-regulatory mechanisms of natural ecosystems and how the functional traits of the soil and plant-associated microbiome may be implemented and promoted in existing agro-ecosystems or preserved when natural ecosystems are converted to agricultural land.
The Research Topic will also introduce novel experimental concepts such as process-oriented omics-approaches and ecosystem modelling, both emphasizing N and P cycling at different spatio-temporal scales in order to better understand the potential of selected soil and plant-associated microbiome for sustainable agriculture.
Keywords: Soil and plant-associated microbiome, Agro-ecosystem resource efficiency, Ecosystem services, Spatio-temporal scales
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