Determining the biogeochemical transformations of organic matter composition in rivers using molecular signatures

Abstract

Inland waters are hotspots for biogeochemical activity, but the environmental and biological factors that govern the transformation of organic matter (OM) flowing through them are still poorly constrained. Here we evaluate data from a crowdsourced sampling campaign led by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to investigate broad continental-scale trends in OM composition compared to localized events that influence biogeochemical transformations. Samples from two different OM compartments, sediments and surface water, were collected from 97 streams throughout the Northern Hemisphere and analyzed to identify differences in biogeochemical processes involved in OM transformations. By using dimensional reduction techniques, we identified that putative biogeochemical transformations and microbial respiration rates vary across sediment and surface water along river continua independent of latitude (18°N−68°N). In contrast, we reveal small- and large-scale patterns in OM composition related to local (sediment vs. water column) and reach (stream order, latitude) characteristics. These patterns lay the foundation to modeling the linkage between ecological processes and biogeochemical signals. We further showed how spatial, physical, and biogeochemical factors influence the reactivity of the two OM pools in local reaches yet find emergent broad-scale patterns between OM concentrations and stream order. OM processing will likely change as hydrologic flow regimes shift and vertical mixing occurs on different spatial and temporal scales. As our planet continues to warm and the timing and magnitude of surface and subsurface flows shift, understanding changes in OM cycling across hydrologic systems is critical, given the unknown broad-scale responses and consequences for riverine OM.

Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers

“…These characteristic distances were then weighted by transformation distances associated with the mass of each molecular formula. While described in detail elsewhere (Buser-Young et al, 2023;Danczak et al, 2021Danczak et al, , 2020Fudyma et al, 2021;Graham et al, 2018), the transformation analysis estimates the presence of putative biochemical transformations by measuring the mass differences between identified peaks which are then related to a database of known and commonly observed biochemical transformations. Relationships between peaks are then established by measuring the number of transformations required for one peak to potentially become another.…”

Opening Doors to Physical Sample Data Discovery, Integration, and Credit

“…Analysis and visualizations from the sample set were incorporated into formally published datasets for longterm preservation and documentation in the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository 55,56 . These datasets were then referenced in the final journal publications associated with the data [57][58][59][60] .…”

Machine Learning Models for Evaluating Biological Reactivity Within Molecular Fingerprints of Dissolved Organic Matter Over Time

“…Moreover, besides the deterministic processes (e.g., microbial processing, photochemistry degradation) influencing the generation, transformation, and transport of individual MFs, the stochastic factors that arise from random events are non-negligible to shape DOM molecular dynamics in both natural systems and biological incubations (She et al, 2023). This stochasticity could be attributed to uncoordinated fluctuations in the rates of generation or conversion (Buser-Young et al, 2023), while the understanding to dynamic contribution of stochasticity during the incubation over time remains lacking.…”