SnoCam

Tools to measure the quantity and composition of gravitationally sinking biological organic matter, via the “biological carbon pump” (BCP) are of increasing importance. Decades of work have established the utility and also the potential methodological deficiencies of sediment traps for the collection of this sinking organic matter. Sediment traps that minimize hydrodynamic biases during particle collection, and underwater imaging devices that can resolve time-dependent fluxes and identify sources of sinking material, are some of the most powerful tools available for direct collection and characterization of BCP fluxes. However, such devices at present are expensive to develop and maintain, and typically operated only by their originating laboratories. Furthermore, few studies have tested the sediment trap platform hydrodynamic effects on sinking particle imagers. The proposed project would build upon work of each of the proposing PIs to develop sediment trapping and particle sensing tools that utilize openly shared software, and hardware designs that are based upon commercially-available components. The first objective of this project is to develop and test a sediment trap controller that would simplify the construction and deployment of neutrally-buoyant sediment traps (NBSTs) based upon commercially-available profiling floats, thus broadening the potential user base of such traps, which are minimally impacted by hydrodynamic effects. The second objective is to integrate with the trap controller a low-cost, upward-looking in situ camera to image sinking particles. Characterizing this camera’s performance under a variety of platform hydrodynamic conditions, and developing software for onboard data reduction, will lay the groundwork for its use to quantify sinking carbon fluxes aboard autonomous platforms. Finally, recognizing that the lower mesopelagic zone (defined here as 500-1000 m) is critical to observations of biological carbon sequestration over long timescales, the third project objective is to optimize these tools for use at these typically-undersampled depths.