Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics

Abstract

The sinking of organic particles produced in the upper sunlit layers of the ocean forms an important limb of the oceanic biological pump, which impacts the sequestration of carbon and resupply of nutrients in the mesopelagic ocean. Particles raining out from the upper ocean undergo remineralization by bacteria colonized on their surface and interior, leading to an attenuation in the sinking flux of organic matter with depth. Here, we formulate a mechanistic model for the depth-dependent, sinking, particulate mass flux constituted by a range of sinking, remineralizing particles. Like previous studies, we find that the model does not achieve the characteristic 'Martin curve' flux profile with a single type of particle, but instead requires a distribution of particle sizes and/or properties. We consider various functional forms of remineralization appropriate for solid/compact particles, and aggregates with an anoxic or oxic interior. We explore the sensitivity of the shape of the flux vs. depth profile to the choice of remineralization function, relative particle density, particle size distribution, and water column density stratification, and find that neither a power-law nor exponential function provides a definitively superior fit to the modeled profiles. The profiles are also sensitive to the time history of the particle source. Varying surface particle size distribution (via the slope of the particle number spectrum) over 3 days to represent a transient phytoplankton bloom results in transient subsurface maxima or pulses in the sinking mass flux. This work contributes to a growing body of mechanistic export flux models that offer scope to incorporate underlying dynamical and biological processes into global carbon cycle models.

Figure 1

Though sinking oceanic particles (inset images) encompass a wide range of shape, porosity, ballast and other characteristics, our model attempts to capture some of the predominant features that influence the shape of the sinking flux profile (red line). Our simplified model is depicted (inset); the spheres represent either solid particles or aggregates. These particles (initial radius a₀), produced within the sunlit euphotic zone (green region extending to z_eu), sink at a rate predicted by Stokes law. They slow as they reach greater depths due to their shrinking volume and increasing water density and would entirely disappear at z_dis. The images of inset particles are sinking phytoplankton, pellets and aggregates captured in particle-preserving gel traps by Dr. Colleen Durkin.

Figure 2

(a) A particle (a_o = 250 μm, α = 0.03) slows as it sinks into denser water (β = 5 × 10⁻⁶ m⁻¹) and is remineralized (r = 0.11 d⁻¹), until disappearing at z_dis = 980 m (Eq. 8). (b) Mass flux profiles (Eqn 9, given the initial size spectrum shown in the inset of panel c, and N_o = 10⁴ particles m⁻²d⁻¹) for particle size classes ranging from a_o = 10 to 250 μm. (c) The total mass flux (eqn 11). Note that for our model, z = 0 represents the base of the euphotic zone.

Figure 3

(a) Initial modeled particle sinking velocity (m d⁻¹) and (b) excess density (ρ_eff − ρ_T) as a function of size (equivalent spherical diameter ESD) for small particles (ρ_p = ρ_eff, black points) and aggregates (gray points) at t=0 released at the base of the euphotic zone. The fluid density ρ_T = 1028 kg m⁻³ and α ranges from 0.01 to 0.1. A fractal dimension of 1.85 and A_f = 1.49 reproduces the flattened w spectrum observed in situ for larger, fluffier aggregates (red dashed lines) with less excess density^,,.

Figure 4

Meridional transects of β reflecting (a) pressure-driven absolute density, and (b) potential density. These values were computed from the WOA09 database from zonal averages between 10.5 to 28.5 ^oW in the Atlantic Ocean. Thick black lines indicate the density contours, and the red line is the mean euphotic depth from a climatological SeaWIFS K490 product. β is calculated over over the depth range examined in our model from z_eu to 1000 m.

Figure 5

Time-series of potential density -1000 kg m^-3 (σ_t, colors) from ARGO float 6391bermuda (from the chemical sensor group at MBARI www.mbari.org) with contour lines indicating the depth of neutral density for a compressible (thick line) and incompressible (thin line) particle with density ρ_p = 1027 kg m⁻³.

Figure 6

(a) The change in size of a particle of initial radius a_o,i = 250 μm, r = 0.11 d⁻¹, as it is consumed according to eqn (2) for the three remineralization cases n = 0, n = 2 and n = 3. (b) The change in volume as a function of depth for a single size class of particles with a_o,i = 250 μm. (c) The resulting flux profile obtained from integrating over a range of size classes with a size spectral slope of −3, as in Fig. 2.

Figure 7

Variety of flux profiles (solid lines) that are obtained from Equations 10 and 11 spanning the observed ranges of (a) excess particle density factor α, (b) initial size spectral slope p, (c) remineralization rate r and (d) vertical density change β. In each case, one parameter is varied, and the others are kept fixed at α = 0.03, p = − 3, r = 0.05 d⁻¹ and β = 5 × 10⁻⁶ m⁻¹ (black lines). For panel (d) we overlay (in gray) flux profiles obtained with α = 0.005 to demonstrate that the profiles are sensitive to β when α is very small. The transfer efficiency T₁₀₀ is shown with open circles intersecting each profile, with its magnitude defined by the axis on the right hand side of the plots.

Figure 8

A size-dependant particle density can be used to counteract the flattening effect seen with depth in the model. (a) The excess density that results from a constant α = 0.03 (blue line) and α that linearly decreases from 0.125 to 0.004 over the specified log-distribution of particle sizes (red line). (b) The size spectrum is shown to flatten with depth in the constant α case. (c) With a size-dependant α, this effect is markedly reduced. A similar result can be achieved with an r that increases with increasing particle size (not shown).

Figure 9

Time evolution of the vertical flux profile as the slope of the particle size spectrum is varied linearly in time from p = −2 on day 16 to p = −4.5 on day 19, after which it is held constant. The total mass flux exiting the euphotic layer is held constant and other parameters are fixed at α = 0.03, r = 0.05 d⁻¹, and β = 5 × 10⁻⁶ m⁻¹.

Figure 10

Time-evolution of the particle size spectrum (PSD) at z = 500 m as the number spectral slope at the surface was varied from p = −2 to p = −4.5. The largest particles transition more rapidly to the new steady-state, and the smallest particles transition more slowly.