Work Package 8
A biogeochemical model for Benguelan sediments
In the Benguela upwelling system, the elevated flux of organic detritus to the seabed leads to the formation of hydrogen sulfide and extensive communities of large sulfide oxidizing bacteria on the seafloor (Schulz et al., 1999). These bacteria oxidize sulfide using nitrate that is stored within their cells to produce either ammonium or N2 as an end product, with additional impacts on the P cycle (Schulz & Schulz, 2005; Dale et al., 2009; Goldhammer et al., 2010; Winkel et al., 2016). Fieldwork and modelling in the Peruvian upwelling have shown that these bacteria exert a major control on the net N and P source/sink function (Dale et al., 2016; Lomnitz et al., 2016). This sub-project will lead to the development of a biogeochemical non-steady state model of Benguela sediments.
General Questions and Research topics:
- What are the key processes and rates of benthic elemental turnover (C,N,P,S, trace metals) in the Benguela upwelling system and their sensitivity to varying environmental conditions?
The model (Dale et al., 2016) will serve as a focal point for synthesizing the biogeochemical data gathered in the sediments. The field data will be used to carefully constrain major transport processes (e.g. diffusion, burial, bioturbation) and biogeochemical process and reaction rates. This will include a comprehensive N cycle including an explicit description of the microbial nitrate reservoir to quantify the rate of nitrate reduction as well as its contribution to benthic ammonium and N2 release through the oxygen minimum zone. A novel focus will be the consideration of benthic N and P storage, tipping points for sulfide release and feedbacks under temporally varying environmental conditions, aided by the perturbation experiments carried out in WP 5 and 6. The in situ benthic lander experiments will provide further crucial information on time-scales of these feedbacks and the corresponding benthic fluxes needed to validate the model. An improved understanding of longer-term benthic-pelagic coupling will be achieved by forcing the model with data from the time-series station. It is expected that this will highlight the key reactions the N, P and S cycles and allow a reduced complexity benthic model to be developed. This simple model can then be coupled to the 3D ecosystem model of the BUS to allow for more realistic regional upscaling of benthic processes and fluxes.