Modeling the nitrogen cycle one gene at a time

Victoria Coles1, Michael R Stukel2, Raleigh R Hood3, Mary Ann Moran4, John H Paul5, Brandon Satinsky4, Brian Zielinski6 and Patricia L Yager4, (1)University of Maryland Center for Environmental Science, Horn Point Laboratory, Cambridge, MD, United States, (2)Florida State University, Earth, Ocean and Atmospheric Science, Tallahassee, FL, United States, (3)University of Maryland Center for Environmental Science, Cambridge, MD, United States, (4)University of Georgia, Athens, GA, United States, (5)University of South Florida, College of Marine Science, St. Petersburg, FL, United States, (6)University of South Florida St. Petersburg, St Petersburg, FL, United States
Abstract:
Marine ecosystem models are lagging the revolution in microbial oceanography. As a result, modeling of the nitrogen cycle has largely failed to leverage new genomic information on nitrogen cycling pathways and the organisms that mediate them. We developed a nitrogen based ecosystem model whose community is determined by randomly assigning functional genes to build each organism’s “DNA”. Microbes are assigned a size that sets their baseline environmental responses using allometric response curves. These responses are modified by the costs and benefits conferred by each gene in an organism’s genome. The microbes are embedded in a general circulation model where environmental conditions shape the emergent population. This model is used to explore whether organisms constructed from randomized combinations of metabolic capability alone can self-organize to create realistic oceanic biogeochemical gradients. Community size spectra and chlorophyll-a concentrations emerge in the model with reasonable fidelity to observations. The model is run repeatedly with randomly-generated microbial communities and each time realistic gradients in community size spectra, chlorophyll-a, and forms of nitrogen develop. This supports the hypothesis that the metabolic potential of a community rather than the realized species composition is the primary factor setting vertical and horizontal environmental gradients. Vertical distributions of nitrogen and transcripts for genes involved in nitrification are broadly consistent with observations. Modeled gene and transcript abundance for nitrogen cycling and processing of land-derived organic material match observations along the extreme gradients in the Amazon River plume, and they help to explain the factors controlling observed variability.