INFERRING MULTITROPHIC CARBON DYNAMICS IN THE BERMUDA ATLANTIC TIME-SERIES STUDY USING A MECHANISTIC ECOSYSTEM MODEL

Modern sampling and analysis tools generate extensive high-resolution data on microbial communities, including DNA sequences, cell abundances, and metabolite concentrations. Yet direct observation of microbial interactions, which are essential for a quantitative, mechanistic understanding, and the pathways through which carbon flows between them, remain difficult to observe directly and require quantitative inference. To address this gap, we integrated four years of data from the Bermuda Atlantic Time-series Study (BATS) into FluxNet, a mechanistic ecosystem model that estimates carbon fluxes among species and trophic compartments. The model represents approximately forty of the most abundant taxa across heterotrophic bacteria, phytoplankton, heterotrophic protists, and zooplankton, as well as particulate and dissolved organic matter, and reconstructs interaction networks by constraining carbon transfer in a mass-balanced framework. To capture vertical structure, the upper two hundred meters of the water column are divided into dynamically varying surface, deep chlorophyll maximum, and upper mesopelagic layers, allowing analysis of vertical transport and export processes. The resulting time-resolved flux fields provide a framework for examining how carbon moves within and between layers, how resources are divided among trophic groups, and when export toward deeper waters intensifies. By combining detailed time series observations with a mechanistic, multispecies framework, this approach provides a quantitative view of multitrophic carbon pathways in the surface ocean and offers a basis for interpreting ecosystem variability at BATS.

Presentation Preference: Standard Oral (12 Minutes)

Primary Presenter: Falk Eigemann, TU Berlin (falkeigemann@gmail.com)

Authors:

Falk Eigemann, TU Berlin  (eigemann@tu-berlin.de)

Jutta Hoffmann, TU Berlin  (jutta.hoffmann@tu-berlin.de)

Leocadio Blanco-Bercial, Bermuda Institute of Ocean Science  (Leocadio@asu.edu)

Fabian Wittmers, Oregon State University  (fabian.wittmers@oregonstate.edu)

Kevin Vergin, Microbialdnaanalytics  (kevin@microbialdnaanalytics.com)

Krista Longnecker, Woods Hole Oceanographic Institution  (klongnecker@whoi.edu)

Alexandra Worden, Marine Biological Laboratory  (azworden@mbl.edu)

Stephen Giovannoni, Oregon State University  (steve.giovannoni@oregonstate.edu)

Elizabeth Kujawinski, Woods Hole Oceanographic Institution  (ekujawinski@whoi.edu)

Ferdi Hellweger, TU Berlin  (ferdi.hellweger@tu-berlin.de)