Microbial trait-based approaches for agroecosystems

Conventional agricultural practices negatively impact soil biodiversity, carbon stocks, and greenhouse gas emissions in ways that make them unsustainable for supporting future supply of food and fiber. Better management of agrobiodiversity will likely play a critical role in transitioning towards more sustainable practices. In particular, innovation and developments targeting the aboveground and belowground components of agroecosystems should be informed by frameworks and approaches that harness the –in particular functional– diversity of complex microbial communities. Here, we review and discuss microbial trait-based approaches that will help us understand and steer agroecosystem functioning in the face of global change. We highlight how trait-based approaches can improve agricultural practices related to soil functioning (e.g. soil fertility and aggregation); climate regulation (e.g. carbon storage and greenhouse gas emissions) and adaptation to climate change; plant health; and reduction of contaminant-related hazards for human health. We also consider how microbial trait-based approaches can be used as a tool to improve cultivated plant performance through artificial selection and microbiome engineering. Last, we discuss the inherent obstacles associated with the development and implementation of trait-based approaches owing to strong interactions within microbial communities and linkages between plants and the soil environment. Despite these obstacles, microbial trait-based approaches hold promise for the sustainable management of agricultural ecosystems needed to feed and nourish a rapidly growing human population

Microbial trait-based approaches for agroecosystems

International audienceConventional agricultural practices negatively impact soil biodiversity, carbon stocks, and greenhouse gas emissions in ways that make them unsustainable for supporting future supply of food and fiber. Better management of agrobiodiversity will likely play a critical role in transitioning toward more sustainable practices. In particular, innovation and developments targeting the aboveground and belowground components of agroecosystems should be informed by frameworks and approaches that harness the-in particular functional diversityof complex microbial communities. Here, we review and discuss microbial trait-based approaches that will help us understand and steer agroecosystem functioning in the face of global change. We highlight how trait-based approaches can improve agricultural practices related to soil functioning (e.g., soil fertility and aggregation); climate regulation (e.g., carbon storage and greenhouse gas emissions) and adaptation to climate change; plant health; and reduction of contaminant-related hazards for human health. We also consider how microbial trait-based approaches can be used as a tool to improve cultivated plant performance through artificial selection and microbiome engineering. Last, we discuss the inherent obstacles associated with the development and implementation of trait-based approaches owing to strong interactions within microbial communities and linkages between plants and the soil environment. Despite these obstacles, microbial trait-based approaches hold promise for the sustainable management of agricultural ecosystems needed to feed and nourish a rapidly growing human population

Microbial trait-based approaches for agroecosystems

Conventional agricultural practices negatively impact soil biodiversity, carbon stocks, and greenhouse gas emissions in ways that make them unsustainable for supporting future supply of food and fiber. Better management of agrobiodiversity will likely play a critical role in transitioning toward more sustainable practices. In particular, innovation and developments targeting the aboveground and belowground components of agroecosystems should be informed by frameworks and approaches that harness the—in particular functional—diversity of complex microbial communities. Here, we review and discuss microbial trait-based approaches that will help us understand and steer agroecosystem functioning in the face of global change. We highlight how trait-based approaches can improve agricultural practices related to soil functioning (e.g., soil fertility and aggregation); climate regulation (e.g., carbon storage and greenhouse gas emissions) and adaptation to climate change; plant health; and reduction of contaminant-related hazards for human health. We also consider how microbial trait-based approaches can be used as a tool to improve cultivated plant performance through artificial selection and microbiome engineering. Last, we discuss the inherent obstacles associated with the development and implementation of trait-based approaches owing to strong interactions within microbial communities and linkages between plants and the soil environment. Despite these obstacles, microbial trait-based approaches hold promise for the sustainable management of agricultural ecosystems needed to feed and nourish a rapidly growing human population

Microbial minorities modulate methane consumption through niche partitioning

Microbes catalyze all major geochemical cycles on earth. However, the role of microbial traits and community composition in biogeochemical cycles is still poorly understood mainly due to the inability to assess the community members that are actually performing biogeochemical conversions in complex environmental samples. Here we applied a polyphasic approach to assess the role of microbial community composition in modulating methane emission from a riparian floodplain. We show that the dynamics and intensity of methane consumption in riparian wetlands coincide with relative abundance and activity of specific subgroups of methane-oxidizing bacteria (MOB), which can be considered as a minor component of the microbial community in this ecosystem. Microarray-based community composition analyses demonstrated linear relationships of MOB diversity parameters and in vitro methane consumption. Incubations using intact cores in combination with stable isotope labeling of lipids and proteins corroborated the correlative evidence from in vitro incubations demonstrating γ-proteobacterial MOB subgroups to be responsible for methane oxidation. The results obtained within the riparian flooding gradient collectively demonstrate that niche partitioning of MOB within a community comprised of a very limited amount of active species modulates methane consumption and emission from this wetland. The implications of the results obtained for biodiversity–ecosystem functioning are discussed with special reference to the role of spatial and temporal heterogeneity and functional redundancy