NN2O

The main aim of this project is to identify N2O uptake in above ground vegetation in Boreal coniferous forests, and peatlands and forests in different climatic zones to make comparison, and via that, to understand the importance of plant-microbe interactions and their contribution on N2O metabolism.

More specifically, we will characterize (1) N2O consuming microbiome of different above ground vegetation;(2) the microbial functions metabolizing N2O in vegetation; and (3) their dynamics associated with spatially and seasonally variable environmental conditions. Diversities and community structures of N2O consuming microbes will be analyzed by functional gene targeted PCR and novel targeted metagenomics for microbial nitrogen (N) cycling genes from plant and soil samples collected from the study sites across the transect from temperate to arctic region and along the growing seasons. The N2O fluxes, microbial activity and diversity data of vegetation will be compared with the soil chemical, metabolic functions and plant community composition and coverage data, to make regional estimations of N2O consumption in vegetation and it’s impact on overall N2O budget of the ecosystem. The project generates novel ideas and methodologies for sustainable peatland and forestry management, and promote spin-off of innovations and products activating microbial and plant N2O sequestration management strategies and technological applications.

This study aims to explore the impact of N2O-consuming microbes in the above-ground vegetation, and to solve the role of activity of these microbes on regional scale N2O budgets, to understand their importance as a N2O sink. The spatially and seasonally variable fluxes will be modelled to understand the role of plant phyllospheric and cryptogamic cover samples on N2O dynamics at the ecosystem level. The study includes handling of N2O flux and environmental variable data collected from different study sites across the Europe. The estimation of regional contribution of vegetation on N2O fluxes will be done during colaboration. Validation of calculation tools and collecting data sources will be done together. UEF can use computing infrastructure and access databases needed for modelling purposes at Purdue University. The project includes data analyses, modelling and subsequent preparation of publications.