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Proceedings of the National Academy of SciencesEcologyPeer-reviewed journal article

Ecological dynamics explain modular denitrification in the ocean

Xin SuniD, Pearse BuchananiD, Irene H. ZhangiD, Magdalena San RomániD, Andrew R. BabbiniD, Emily J. ZakemiD

PDFDOIPreprint

Abstract

Microorganisms in marine oxygen minimum zones (OMZs) drive globally impactful biogeochemical processes. One such process is the multi-step denitrification, the dominant pathway for bioavailable nitrogen (N) loss and nitrous oxide (N2O) production. Denitrification-derived N loss is typically measured and modeled as a single step, but observations reveal that most denitrifiers in OMZs contain only subsets ("modules") of the complete pathway. Here, we identify the ecological mechanisms sustaining diverse denitrifiers, explain the observed prevalence of certain modules, and examine the implications for N loss. We describe microbial functional types carrying out diverse denitrification modules by their underlying redox chemistry, constraining their traits with thermodynamics and pathway length penalties, in an idealized OMZ ecosystem model. Biomass yields of single-step modules increase along the denitrification pathway when growth is limited by organic matter (OM), explaining the viability of populations respiring nitrite and N2O in a nitrate-filled ocean. Results predict denitrifier community succession along environmental gradients: shorter versus longer modules are favored when OM versus N limits growth, respectively, suggesting a niche for the NO3-{longrightarrow}NO2- module in free-living communities and for the complete pathway in organic particles, consistent with observations. The model captures and mechanistically explains the observed dominance and higher oxygen tolerance of the NO3-{longrightarrow}NO2- module. Results also capture observations that nitrate is the dominant source of N2O. These results advance the mechanistic understanding of the relationship between microbial ecology and N loss, which is essential for accurately predicting the oceans future.

Citations
34
FWCI
6.80
Field percentile
top 2%

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