Marine particle dynamics : sinking velocities, size distributions, fluxes, and microbial degradation rates

Abstract

The sinking flux of particulate matter into the ocean interior is an oceanographic phenomenon that fuels much of the metabolic demand of the subsurface ocean and affects the distribution of carbon and other elements throughout the biosphere. In this thesis, I use a new suite of observations to study the dynamics of marine particulate matter at the contrasting sites of the subtropical Sargasso Sea near Bermuda and the waters above the continental shelf of the Western Antarctic Peninsula (WAP). An underwater digital camera system was employed to capture images of particles in the water column. The subsequent analysis of these images allowed for the determination of the particle concentration size distribution at high spatial, depth, and temporal resolutions. Drifting sediment traps were also deployed to assess both the bulk particle flux and determine the size distribution of the particle flux via image analysis of particles collected in polyacrylamide gel traps. The size distribution of the particle concentration and flux were then compared to calculate the average sinking velocity as a function of particle size. I found that the average sinking velocities of particles ranged from about 10-200 m d-and exhibited large variability with respect to location, depth, and date. Particles in the Sargasso Sea, which consisted primarily of small heterogeneous marine snow aggregates, sank more slowly than the rapidly sinking krill fecal pellets and diatom aggregates of the WAP. Moreover, the average sinking velocity did not follow a pattern of increasing velocities for the larger particles, a result contrary to what would be predicted from a simple formulation of Stokes' Law. At each location, I derived a best-fit fractal correlation between the flux size distribution and the total carbon flux. The use of this relationship and the computed average sinking velocities enabled the estimation of particle flux from measurements of the particle concentration size distribution. This approach offers greatly improved spatial and temporal resolution when compared to traditional sediment trap methods for measuring the downward flux of particulate matter. Finally, I deployed specialized in situ incubation chambers to assess the respiration rates of microbes attached to sinking particles. I found that at Bermuda, the carbon specific remineralization rate of sinking particulate matter ranged from 0.2 to 1.1 d', while along the WAP, these rates were very slow and below the detection limit of the instruments. The high microbial respiration rates and slow sinking velocities in the Sargasso Sea resulted in the strong attenuation of the flux with respect to depth, whereas the rapid sinking velocities and slow microbial degradation rates of the WAP resulted in nearly constant fluxes with respect to depth.

The multiple fates of sinking particles in the North Atlantic Ocean

“…A substrate‐specific respiration rate ( k R ; units of mol C respired :mol POC d −1 ) was determined from these measurements according to an adaptation of McDonnell []: where r pa and r col are volumetric respiration rates from the particle‐attached and water column samples, respectively, calculated by simple linear regression from replicate shipboard incubations; V inc is the incubation volume (300 mL); POC trap is the quantity of POC used in the incubation; and is a molar respiratory quotient for the remineralization of organic matter at depth (we applied a value of 117/170) [ Anderson and Sarmiento , ].…”

The Interpretation of Particle Size, Shape, and Carbon Flux of Marine Particle Images Is Strongly Affected by the Choice of Particle Detection Algorithm

“…Object detection algorithms, using supervised learning, use previously labeled images to learn the visual characteristics of known objects in order to identify similar objects in new data (Zhao et al, 2019). For marine snow and zooplankton imaging, edge detection algorithms such as the Sobel and Canny algorithms have been proven to be useful (Sosik and Olson, 2007;McDonnell, 2011;Thompson et al, 2012;Yu et al, 2016;Ohman et al, 2019).…”

Three-Dimensional Imaging Lidar for Characterizing Particle Fields and Organisms in the Mesopelagic Zone

“…Of the 100 Gt of organic carbon taken up by ocean surface waters per year, up to 10% is transferred to the mesopelagic (similar magnitude as fossil fuel emissions) (Gardner et al, 2000;Giering et al, 2014Giering et al, , 2018. Without this carbon export mechanism, the concentration of CO 2 in the atmosphere would be an estimated 200 ppm higher than present day levels (McDonnell, 2011;Davison et al, 2013;Volk and Hoffert, 2013). This process, known as the "biological pump" is controlled by the productivity of primary producers in the surface ocean and active/passive downward transport of organic and inorganic composite material.…”

“…This process, known as the "biological pump" is controlled by the productivity of primary producers in the surface ocean and active/passive downward transport of organic and inorganic composite material. Current estimates suggest, up to 90% of surface water detrital material is recycled, consumed, and respired before reaching 1,000 m (Stemmann et al, 2008;McDonnell, 2011;Davison et al, 2013;Hansen and Visser, 2016). Understanding the role of the mesopelagic zone (bottom of euphotic zone to 1,000 m) in mediating remineralization and transport to the deep ocean is currently a subject of intense research (Giering et al, 2019;Briggs et al, 2020).…”