Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver nutrient and energy cycles natural ecosystems. Recent advances omics technologies enabled high-throughput generation molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM becoming more readily available, particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as promising approach due its ability predict degradation respiration rates from chemical formulae compounds. This model implicitly assumes all detected compounds are bioavailable, aerobic driven solely by thermodynamics. Despite demonstrations previous studies, these assumptions may not universally valid because complex process governed multiple factors. To identify key drivers respiration, we performed comprehensive analysis diverse systems using Fourier-transform ion cyclotron resonance mass spectrometry associated measurements collected Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support our argument, found incorporation samples into SXTM resulted poor correlation between predicted measured rates. The data-model consistency was significantly improved selective use small subset (i.e., only about 5%) identified an optimization method. Through subsequent comparative (which presume bioavailable) against full set compounds, three traits potentially determine bioavailability, including: (1) favorability (2) number C atoms contained carbon/nitrogen (C/N) ratio. We factors serve “filters” with undesirable properties any strictly excluded bioavailable fraction. work highlights importance accounting interplay among increase predictive power ecosystem