Understanding the links between pelagic microbial ecosystems and organic matter cycling in the changing Arctic

Longer ice-free periods and thinner sea-ice increase light availability, enhancing phytoplankton production, which may also be further stimulated by increased carbon dioxide. We have assembled a multidisciplinary UK/German team to address this NERC/BMBF Arctic call with a renowned track record of pioneering research concerning the structure and function of marine pelagic ecosystems, including extensive research in the Arctic. This project has the overarching aim to improve our understanding of how short-term (e.g. seasonal- scale) and long-term (e.g. climate-driven) changes in the physical environment of the Arctic Ocean are impacting pelagic microbial ecosystems and how these affect current and future organic matter (OM) biogeochemistry. The focus of our activities principally addresses Challenge 1 "To develop quantified understanding of the structure and functioning of Arctic ecosystems". Our multidisciplinary team with expertise in marine microbial ecology, OM biogeochemistry, polar plankton ecology, and ecosystem modelling will fully characterise the microbial base (archaea, bacteria, protists including phytoplankton and fungi) of the pelagic Arctic food web in relation to OM cycling. Through a comprehensive multi-location and multi-seasonal cruise programme we will address major knowledge gaps in the links between Arctic microbial ecosystem structure and function across a broad range of sea-ice environments. Our sampling strategy, including the rarely sampled winter and early spring, will allow us to quantify impacts of Arctic seasonality on the structure and functioning of microbial ecosystems in relation to OM cycling, allowing us to track major changes in autotrophic and heterotrophic production. Combining observation and modelling, we will analyse the underlying mechanisms that impact microbial dynamics and subsequent OM cycling on seasonal scales. The model setup will integrate forcing data and results of NEMO-MEDUSA simulations. Data-model synthesis will enable us to resolve and constrain processes that remain either unresolved or are assumed constant in MEDUSA. Our model results will thus specify uncertainty ranges that may be accounted for in future projections of the Arctic with NEMO-MEDUSA and the UK Earth System Model (UKESM).