Cooperation, Competition and Carbon: A trait-based modelling approach to microbial mediation of natural dissolved organic carbon storage in the ocean.

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The oceanic inventory of dissolved organic carbon (DOC) is one of the largest active carbon pools at the Earth’s surface, comparable in size to the carbon content of the atmosphere. DOC is directly linked to atmospheric CO2 via microbial respiration and gas exchange at the ocean’s surface, and thus holds a high potential for biological feedbacks in a changing climate. Global biogeochemical models are powerful tools to assess future scenarios, but only gain predictive skill if they are based on mechanistic understanding. Scientists have recently warned that neglecting the role of microorganisms severely reduces predictive skills for future climate scenarios. Current carbon models usually do not take into account the complex microbial interactions with DOC, which is of concern because the marine DOC pool is large, active and has been shown to play a role in the climate system through its direct link to CO2. Current modelling approaches for marine DOC mainly apply prescribed reactivity classes of DOC fractions. While this approach elegantly reproduces present-day DOC concentration, it does not reflect mechanistic processes and thus lacks the flexibility to account for changing environmental conditions. The proposed project aims to identify and implement the microbial traits required to explain the spatiotemporal pattern of present-day marine DOC concentration in a global biogeochemical ocean model. Here we chose an approach in which the microbial community in the model adapts to environmental conditions, a so called self-assembling approach. This approach will be applied to heterotrophic (=DOC degrading) microbial diversity. By including microbial heterotrophic diversity in a global model with a self-assembling approach for the first time, I aim to identify traits and trade-offs relevant for DOC turnover in the ocean. Specific aims include to 1) derive theoretic constraints on the role of DOC in interactions between phytoplankton and heterotrophic microorganisms in a case study, 2) test whether a subset of common traits and trade-offs explains observed global surface DOC concentrations in a global ocean model, and 3) identify and quantify subsurface DOC sources in addition to particle dissolution, as suggested in several previous observational studies (optional). To do that, I propose to spend 12 months at Prof. Mick Follows group at Massachusetts Institute of Technology, MIT, in order to connect my previously developed microbial DOC model to their Darwin model and apply the self-assembling approach to the microbial community that degrades DOC. The project will advance the field by providing an improved understanding on the mechanisms driving natural DOC storage in the ocean by improving the representation of the global marine DOC cycle in a marine carbon cycle model.