Data-Driven Modeling of the Distribution of Diazotrophs in the Global Ocean

Abstract

Diazotrophs play a critical role in the biogeochemical cycling of nitrogen, carbon, and other elements in the global ocean. Despite their well-recognized role, the diversity, abundance, and distribution of diazotrophs in the world's ocean remain poorly characterized largely due to limited observations. Here we update the database of diazotroph nifH gene abundances and assess how environmental factors may regulate diazotrophs at the global scale. Our meta-analysis more than doubles the number of observations in the previous database. Using linear and nonlinear regressions, we find that the abundances of Trichodesmium, UCYN-A, UCYN-B, and Richelia relate differently to temperature, light, and nutrients. We further apply a random forest algorithm to estimate the global distributions of these diazotrophic groups, identifying undersampled potential hot spots of diazotrophy in the South Atlantic and southern Indian Ocean, and in coastal waters. The distinct ecophysiologies of diazotrophs highlighted here argue for separate parameterizations of different diazotrophs in model simulations.