Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
BG4.2 | Microbial-DOM interactions from molecular to basin-wide scales
EDI
Microbial-DOM interactions from molecular to basin-wide scales
Convener: Sinikka Lennartz | Co-conveners: Chiara Santinelli, Gianpiero Cossarini, Hannelore Waska
Dissolved organic matter (DOM) in natural waters represents the main source of energy for heterotrophic prokaryotes. The processes of microbial uptake, respiration and release of DOM ultimately control this large carbon reservoir of more than 600 petagrams of carbon, naturally storing more carbon than all living biomass on earth combined. The mechanisms of DOM production, removal and accumulation remain difficult to quantify, partly due to the large diversity of microbes and molecules and their manifold interactions. In biogeochemical modelling studies, DOM is still over-simplistically parameterized, and identifying individual constituents of the DOM pool as well as linking DOM composition to more easily measured proxies from e.g. optical measurements (chromophoric DOM, CDOM, fluorescent DOM, FDOM) remains challenging. This lack of mechanistic understanding hampers insight into changes of this significant organic carbon reservoir in a future climate. Understanding the main mechanisms regulating the biological availability of DOM is one of the most challenging, but pressing issues in environmental science.
We aim to gather experts in physical, biogeochemical, optical and satellite oceanography from marine and freshwater ecosystems to foster interdisciplinary exchange to gain insight into the cycling of DOM in natural waters. Field, laboratory and modelling studies from the sediment to the sea surface microlayer are welcome. Encouraged submissions include, but are not limited to, experimental studies and field observations along environmental gradients, data science approaches focusing on algorithm development in the DOM context, studies linking microbial and biogeochemical data, as well as biogeochemical modelling approaches.