Incorporation of Microbial Functional Traits in Biogeochemistry Models Provides Better Estimations of Benthic Denitrification and Anammox Rates in Coastal Oceans

Abstract

AbstractMarine benthic nitrogen (N) cycling may vary widely across space and seasons; it is thus needed to make high‐resolution estimations of these important ecosystem processes with a reasonable number of variables. In this study, we determined the benthic denitrification and anammox potentials in two basins, the Bohai Sea and the North Yellow Sea of China in May and November, and evaluated models in predicting these functions with environmental factors and/or microbial gene‐based functional traits. We found that denitrification generally dominated the N loss (54–98%), and that the denitrification rate varied greatly between basins and seasons. The anammox rate was generally higher in the Bohai Sea than in the North Yellow Sea in both seasons, and it made a greater contribution in November (22%) than in May (16%). Among the measured environmental factors, chlorophyll a in bottom waters and sedimentary organic carbon content were the most influential for predicting denitrification and anammox rates, respectively. On the other hand, the alpha diversities and gene abundances of involved bacteria were poorly correlated with the function potentials, indicating that these functional traits could not well explain the functions alone. Upon the incorporation of two gene copy number ratios [nosZ/(nirS + nirK) and nirK/bacterial 16S rRNA genes] into the environmental factor‐parameterized models, however, we found that the predictive powers of the regression models for total N loss, denitrification and anammox rates, and contributions of anammox increased substantially, indicating that taking microbial functional traits into account could make estimations of these N‐cycling functions in coastal ecosystems more accurate.