Settling behavior of marine aggregates - from a modeling perspective

The settling behavior of marine aggregates has substantial effects on the ecology and the biogeochemistry of carbon and nitrogen in the oceans. Due to Their Relatively high sinking speeds, aggregates can be understood of as vehicles for the vertical flux of organic matter in aquatic environments (Karakaş et al., 2009). Moreover, marine aggregates also constitute hot spots of microbial activity and are sites of rapid and efficient turnover of particulate organic carbon in the ocean. In addition, aggregates serve as pray for many microorganisms that the turnover of particulate organic carbon (Iversen & Lampitt, 2020). The microorganisms such as copepods can detect the hydrodynamic signal that is induced by an aggregate while settling. In particular,the influence on the hydrodynamic signal due to the aggregate shape needs further investigation to better understand the feeding mechanisms. This will ultimately help to further the understanding of the turnover of particulate organic carbon in the ocean. Therefore, the following set of research question are addressed:

How does the surface roughness orientation and shape of sinking aggregates affect their hydrodynamics signals?

• How will this influence Both chemical and hydrodynamic cues for zooplankton?

• What size and settling velocities of aggregated fall within the “price range”? - How does roughness orientation and shape impact this?

To answer these questions a numerical CFD model was used based on the open source toolbox OpenFOAM (Open Field Operation and Manipulation). This C ++ based software package provides a wide range of solvers that are readily compiled, but also may be personalized by the user for individual purposes (Schmeeckle, 2014; Bartzke et al., 2018). In order to resolve the flow equations OpenFOAM uses the Finite Volume Method (FVM). The study domain is discretized into a grid of three-dimensional hexagonal elements, over which volume integral formulations of conservation equations are applied. Variables such as the pressure scalar, and velocity vector are stored at the center of each control volume ie, cell of the mesh (Ferziger & Perić, 2002).

Initial model results show that an irregular shaped aggregate seems to alter the flow in a higher quantity and hence, the induced hydrodynamic signal can be detected by a microorganism with a greater chance. Consequently, it can be expected that the pray range ie to which distance an aggregate can be detected by a microorganism can be further classified. It is anticipated that this will help to further the understanding of the feeding mechanisms of microorganisms, and will ultimately contribute to widen the understanding of the turnover of particulate organic carbon in the ocean.

References:

Bartzke, G., Schmeeckle, MW and Huhn, K. (2018) Understanding heavy mineral enrichment using a three-dimensional numerical model. Sedimentology, 65, 561-581.

Ferziger, JH and Perić, M. (2002) Computational methods for fluid dynamics. Springer, Berlin, 200 pp.

Iversen, MH and Lampitt, RS (2020) Size does not matter after all: No evidence for a size-sinking relationship for marine snow. Prog. Oceanogr., 189, 102445.

Karakaş, G., Nowald, N., Schäfer-Neth, C., Iversen, M., Barkmann, W., Fischer, G., Marchesiello, P. and Schlitzer, R. (2009) Impact of particle aggregation on vertical fluxes of organic matter. Prog. Oceanogr., 83, 331-341.

Schmeeckle, MW (2014) Numerical simulation of turbulence and sediment transport of medium sand. J. Geophys. Res. Earth Surf., 119, 1240-1262.