Funded Research - Project Profile: Siegel-01



Project Title: Synthesizing Optically- and Carbon Export-Relevant Particle Size Distributions for the EXPORTS Field Campaign


Project Lead: David (Dave) Siegel, UC Santa Barbara


NRA: 2016 NASA: Ocean Biology and Biogeochemistry


Abstract:

Particle size has fundamental control on the distribution and dynamics of particulate carbon in the upper ocean. Stokes’ law states that particles with larger effective diameters (D) will sink faster than smaller ones determining whether particles are effectively suspended within the water column (D<~100 μm) or are sinking (D>~500μm). Net Primary Production (NPP) enters pelagic ecosystems as suspended particles and these particles (along with CDOM) control the ocean’s optical properties. Further, sinking particles undergo many biotic and abiotic transformations in their size, composition and sinking velocity as they transit from the surface ocean, regulating carbon export and remineralization profiles. This points to the importance of understanding the particle size distribution (PSD) in predicting the fate of NPP, the central goal of EXPORTS. We propose to answer four science questions to develop a predictive understanding of the PSD for both suspended and sinking particles.

1. How do the abundance, composition and productivity of particle source materials regulate the PSD for smaller, optically relevant particle sizes?
2. How do source particle characteristics as well as biotic / abiotic interactions on sinking particles regulate the PSD for larger, carbon export relevant particle sizes?
3. Can the combined size distribution for suspended and sinking particles be modeled using optical data and in particular from satellite ocean color observations?
4. How do energy and carbon derived from phytoplankton NPP cascade through the particle size spectrum?

These four science questions address aspects of many of the EXPORTS Science Questions (SQ) and answers SQ1C and SQ1D directly. We propose an integrated research program of in situ optical and imagery observation (Siegel, Nelson, McDonnell), at-sea characterization and experimentation on collected aggregates (Passow) and numerical modeling (Burd, Siegel). Advances in nearforward angle light scatter (LISST) and in situ imaging (UVP) enable high-resolution profiles of the PSD for both suspended and sinking particulates. Inherent optical and oceanographic properties will be monitored simultaneously to characterize suspended particle composition and oceanic context. We will collect sinking aggregates using the Marine Snow Catcher to characterize their ecological and biogeochemical composition, physical properties as well as their decomposition rates, all of which are needed for modeling. The assembled data set will be the basis of mechanistic numerical models that transform the combined PSD as a function of depth and ecosystem / carbon cycling state. We will test relationships among source materials (phytoplankton, zooplankton feces, etc.) and biotic (zooplankton grazing, etc.) and abiotic (turbulence, density gradients, etc.) disrupters of aggregate distributions. Data available from other EXPORTS investigations (particle export & composition, phytoplankton abundance & composition, NPP, etc.) will be incorporated as needed. For example, we will assess the sinking velocity size spectrum using collected trap samples and our PSD measurements as well as spatiotemporal validated fields of particle export fluxes and PSD transformations from inverse modeling. These data products and models will be distributed to the EXPORTS Science Team and beyond. Our proposal responds primarily to Section 3.1.2.2 (Collection & Analysis of Field Data) of the 2016 ROSES A3 solicitation, but also contributes to Sections 3.1.2.1 (Development of RS Data Products) and 3.1.2.3 (Development of Models).

The Lead-PI (Siegel) was also selected to be the EXPORTS Science Lead.

Keywords: particle size spectra, sinking particle export, aggregate dynamics, remote sensing algorithms


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Post-Doc(s):

  • None


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Student-Undergraduate(s):

  • None


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  • None


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