Integrar Dados Biogeoquímicos e Genómicos para Prever Mudanças no Ciclo do Azoto no Oceano Ártico

In this project, we propose a challenging and timely work plan that aims to integrate genomic data into biogeochemical modeling frameworks. This will address major scientific questions regarding how nitrogen cycling processes and the members of the microbiome involved are likely to respond or adapt to Arctic climate-driven changes, and what feedbacks might be expected from this changing microbiome. The specific scientific goals (SG) are as follows: SG1 - Establish relationships between on one hand, the abundance of Nitrogen taxonomic groups and Nitrogen functional genes with environmental and biogeochemical data, based on Arctic Ocean long-term historical datasets (from 2015 - 2024). In SG1 we hypothesize that the abundance of taxonomic groups and genes associated with the nitrogen cycle are correlated with environmental contextualized data (physical, chemical and biogeochemical) (e.g. Magalhães et al. 2009, Santoro et al. 2010 and references therein). In SG1 we will determine these relationships across Arctic Ocean spatial and temporal scales. SG2 - Determine the relationship between omic data (taxonomic groups, functional gene abundance, and transcription) and the rates of related functions, focusing on N-fixation, nitrification, and denitrification. To accomplish this objective, we will design controlled experiments with water column and sediment samples (WP2). In SG2, we hypothesize that under similar physical-chemical conditions, the rates of N-fixatio, nitrification and denitrification increase with the relative abundance of the microorganisms that mediate these metabolic processes, as well as with the relative abundance and transcription of specific N genes that regulate these processes (e.g. Coles et al. 2017). SG3 - Create a new Genomic and Biogeochemical model by incorporating different layers of omics data into a marine ecosystem biogeochemical model. This objective will be accomplished by improving the representation of nitrogen cycle processes, considering validated relationships from WP1 and WP2 between the relative abundance of N-Cycle microbiome, as well as the relative abundance and transcription of specific N genes regulating these processes. In SG3, we hypothesize that incorporating genomic data into biogeochemical models is a pivotal advancement in our ability to comprehend and predict the intricate dynamics of Arctic Ocean nitrogen processes (Coles et al. 2017). SG4 - Quantify and compare the importance of the water column and sediments for the fjord nitrogen biogeochemical cycle in Kongsfjorden using a novel Genomic and Biogeochemical model. Here, we hypothesize that the Arctic-wide retreat of tidewater glaciers exposes larger areas of sediments along fjords and coastal areas, thereby increasing their contribution to coastal biogeochemistry (e.g. Wadham et al. 2019). SG5 - Predict the effects of warming on the Arctic Ocean nitrogen biogeochemical cycle. In SG5, we hypothesize that processes associated with the nitrogen biogeochemical cycle in Arctic coasts and fjords will intensify with warming, due to the direct effects of temperature on various N metabolisms and microbiome communities. This will lead to a greater contribution of newly exposed sediments after tidewater glacier retreat. We will test this hypothesis through genomic and biogeochemical model scenario analysis.