Regional variability in the vertical flux of particulate organic carbon in the ocean interior

Authors


Abstract

[1] Carbon transport within sinking biogenic matter in the ocean contributes to the uptake of CO2 from the atmosphere. Here we assess the extent to which particulate organic carbon (POC) transport to the ocean’s interior can be predicted from primary production or export flux. Relationships between POC flux and depth are generally described by a uniform power law or rational decrease with depth, scaled to new or total primary production of POC. While these parameterizations of flux are used in most quantitative biogeochemical models, they are based on data sets from a limited geographic and depth range. We examine these relationships through a review of parameters derived from 14C uptake experiments, regional remote sensing, 234Th studies, nitrogen balances, and sediment trap records. Ocean regions considered include sites studied by the Joint Global Ocean Flux Study, Hawaii Ocean Time-series, and Bermuda Atlantic Time-series Study programs and involve observed and radiochemically corrected flux to depth. We demonstrate regional variability in the efficiency of the biological pump to transport organic carbon from surface waters to the ocean’s interior. Commonly applied flux relationships, while representative of some areas of the ocean, generally overestimate flux to depth. We estimate that the fraction of carbon transported as POC to depths greater than 1.5 km ranges between 0.10 and 8.8% (1.1% average) of primary production and between 0.28 and 30% (5.7% average) of export from the base of the euphotic zone. We develop empirical parameterizations of flux to depth using region-specific constants. Using a one-dimensional ocean model, we predict that the residence time of biogenic carbon may vary by up to 2 orders of magnitude depending on the regional efficiency of export and vertical transport.

1. Introduction

[2] The flux of organic matter from surface waters to the deep ocean has a direct influence on the partitioning of CO2 between the ocean and atmosphere. This biological carbon pump includes three interrelated processes: primary production, export, and flux to depth. Primary production in surface waters, fueled by sunlight and nutrients, converts dissolved inorganic carbon to particulate organic matter (POM) and enhances the ocean’s ability to take up CO2 from the atmosphere. POM is exported from surface waters through a variety of processes, including consumption and repackaging by zooplankton and fish into fecal pellets, particle aggregation, and zooplankton migration and excretion at depth. As exported POM sinks within the ocean’s interior, mesopelagic bacteria and zooplankton oxidize the organic components back into their dissolved inorganic constituents. A small portion of sinking organic matter reaches the seafloor, where it is either remineralized, supporting benthic biological activity, or buried in the geologic record.

[3] Determining the fate of organic matter sinking below the photic zone is crucial to understanding the role of the biological pump in the global carbon cycle and may have a role in determining oceanic sequestration of anthropogenic CO2, especially in the context of changing ocean circulation [Kurz and Maier-Reimer, 1993; Sarmiento et al., 1998; Pahlow and Riebesell, 2000]. In general, the greater the depth at which sinking organic carbon is remineralized, the longer time it takes to return to the photic zone as dissolved CO2, where it may reenter atmospheric carbon cycle. Organic carbon which reaches the deep ocean is entrained in water masses that have longer flow pathways back to the surface and smaller advective water velocities than in the upper ocean. The ventilation of disphotic and aphotic ocean waters occurs on timescales ranging from annual to hundreds years in the upper ocean (∼0.1–1 km) to up to 1000 years in the deep ocean (>1.5 km). Thus, to describe the residence time of biogenic carbon in the ocean, the depth of remineralization must be known.

[4] The intensity of this biological pump depends on several variables, including the level of photosynthetic production, the amount of zooplankton grazing, and the degree of oxidative remineralization at different depths in the water column. Furthermore, photosynthetic production is controlled by the availability of light, nutrients, and trace metals, as well as phytoplankton speciation, temperature, and grazing. At steady state, nutrients removed from surface waters in the form of descending particulate matter are balanced by the upward advective and diffusive supply of dissolved nutrients. The upwelled nutrients support new production [Eppley and Peterson, 1979] in surface waters and are supplied by the remineralization of sinking organic matter.

[5] In this paper we reevaluate relationships between primary production, export, and flux to depth. We present evidence for variability in the vertical flux of organic matter within the ocean that is not accounted for by currently applied flux algorithms. We develop empirical algorithms with varied constants to predict flux to depth in different ocean regions.

2. Previous Flux to Depth Relationships

[6] The two most commonly applied descriptions of oceanic particulate organic carbon (POC) flux are that of Suess [1980] (equation (1)) [see also Six and Maier-Reimer, 1996; Dymond et al., 1997; Paerl, 1997; Soltwedel, 1997; Petsch and Berner, 1998; Sigman et al., 1998; Tyrell, 1999] and that of Martin et al. [1987] (equation (2)) [see also Sarmiento and Le Quere, 1996; Brewer et al., 1997; Emerson et al., 1997; Druffel et al., 1998; Lee et al., 1998; Sarmiento et al., 1998; Hedges et al., 1999; Buesseler et al., 2000; Fischer et al., 2000].

equation image
equation image

Flux to depth Cflux(z) is described as a function of the primary production of organic carbon in surface waters Cprod or the export of organic carbon Cexport from the base of the photic zone z0, scaled to depth below the sea surface z.

[7] The Suess [1980] rational equation was determined from 14C-based primary production and sediment trap flux measurements, collected from the subtropical eastern Pacific and northwestern Atlantic at depths between 50 and 5400 m (Figures 1 and 2). The specific relationship between primary production and particle flux out of the euphotic zone is unclear [Knauer et al., 1984a]. The inability of primary production to predict flux in many areas [Bishop, 1989; Boyd and Newton, 1995; Karl et al., 1996; Lampitt and Antia, 1997] suggests that the magnitude of primary production may not be the most important factor in determining flux to depth [Boyd and Newton, 1999]. The flux to depth relationship of Martin et al. [1987], based on export, is thought to be a more accurate parameterization of flux to depth [Bishop, 1989; Boyd and Newton, 1999; Lampitt and Antia, 1997].

Figure 1.

Locations of flux to depth measurements derived from sediment traps used in this study (open circles). The plus signs and crosses indicate the sample locations used by Suess [1980] and Martin et al. [1987], respectively. OSP, Ocean Station Papa; HOT, Hawaii Ocean Time-Series; BATS, Bermuda Atlantic Time-Series Study; NABE, North Atlantic Bloom Experiment.

Figure 2.

Global ocean annual sediment trap POC flux versus depth used by Suess [1980] and Martin et al. [1987] and in this paper (solid, shaded, and open circles, respectively; references in Table 1). Dotted horizontal lines indicate depth bins used in regional correlation analysis.

[8] The Martin et al. [1987] normalized power function is a “best fit” derived from sediment trap data collected in the low-latitude to midlatitude east Pacific from depths between 100 and 2000 m (Figures 1 and 2). The exponent (−0.858) has been shown to vary within and between ocean basins [e.g., Banse, 1994; Karl et al., 1996; Usbeck, 1999], suggesting that flux cannot be described by variability in export alone. However, the Martin et al. [1987] relationship was adopted by the Ocean Carbon Model Intercomparison Project (OCMIP) project as a component of the “standard” OCMIP biology model. Global ocean models commonly describe flux to depth using the fixed parameters shown in (1) and (2). The global variability of the relationships between POC flux to depth and export or primary production has not previously been assessed.

3. Methods

3.1. Data Selection

[9] We assess the ability of the currently applied Suess [1980] and Martin et al. [1987] algorithms to predict flux to depth. We apply primary production estimates predominantly derived from 14C uptake experiments, and we apply export estimates derived from several methods including thorium isotope uptake experiments, f ratios, and mass balances. Flux predicted by the Suess [1980] and Martin et al. [1987] relationships is compared to sediment trap measurements from different ocean regions. We use the data outlined above to generate new empirical region-specific flux algorithms. The variability of ocean carbon storage predicted by the region-specific flux algorithms is assessed in a one-dimensional ocean model.

[10] Regions were selected on the basis of the availability of primary production, export, and multiple flux to depth estimates to include a variety of physical and biogeochemical provinces. Process studies include the North Atlantic Bloom Experiment (NABE), equatorial Pacific, and Arabian Sea Joint Global Ocean Flux Study (JGOFS) programs. Time series studies include those from the Sargasso Sea/Bermuda Atlantic Time-Series Study (BATS), northeast subarctic Pacific/Ocean Station Papa (OSP), and north central Pacific gyre/Hawaii Ocean Time-Series (HOT). Data selection and filtering are outlined in sections 3.2 and 3.3.

3.2. Estimating Flux to Depth Using Sediment Trap Data

[11] Problems associated with using sediment traps to characterize flux include hydrodynamic biases [Lorenzen et al., 1981; Baker et al., 1988; Buesseler, 1991; Gust et al., 1992, 1994; Siegel et al., 1990; Siegel and Deuser, 1997], zooplankton migration [Longhurst and Harrison, 1988; Walsh et al., 1988; Dam et al., 1995], sample contamination by swimmers [Lee et al., 1988; Karl and Knauer, 1989; Michaels et al., 1990], sample degradation [Knauer et al., 1984b; Honjo, 1990; Honjo et al., 1995], and brine addition [Macintyre et al., 1995; Gardner, 2000]. Hence the accuracy of sediment traps is debated [Jurg, 1996; Gust and Kozerski, 2000]. Reported errors associated with these caveats are variable; some arguably decrease with increasing depth below the photic zone [Gardner, 2000].

[12] The use of sediment traps for measuring the flux of settling particles to the deep ocean (>1.5 km) has been validated by 230Th and 231Pa calibration studies [Scholten et al., 2001; Yu et al., 2001]. These radionuclide studies suggest that sediment traps may often undersample fluxes within the mesopelagic zone (<1.5 km). With the exception of the California margin, Yu et al. [2001] found that a trapping efficiency of 40% is a typical minimum value for the pelagic upper ocean. To account for the potential undertrapping error, we perform our analyses both with and without this correction factor applied to samples from within the mesopelagic zone. In particular, radiochemically calibrated fluxes are calculated to be the observed flux divided by 0.4. This trapping efficiency estimate may be uncertain in part because of the variable incorporation of radionuclides on particles of different sizes [Gardner, 2000; Yu et al., 2001].

[13] Data from ocean sediment trap deployments of the past 20 years are compiled in Table 1 and Figures 1 and 2. The following criteria are used in selecting sediment trap data for this study: (1) All values are from depths greater than the local photic zone and mixed layer depth maximum, (2) data from within 200 m of the seafloor are excluded to avoid contamination by sediment resuspension, (3) sediment traps located within coastal/shelf regions (generally, total water depths <500 m) are excluded to avoid input of terrigenous organic matter, and (4) data are included only if flux to depth is measured throughout an entire year. Exceptions to criterion 4 occur occasionally where samples were collected for a periods shorter than a full year. Accordingly, taking into account seasonal bias, the calculated flux is reported as a minimum if the samples were collected during low-flux periods or as a maximum if they were collected during high-flux periods. The Suess [1980] and Martin et al. [1987] relationships are each based on less than 50 sediment trap data points, of which >80% do not meet the criteria listed above and are not included. Our analysis includes 180 new sediment trap annual flux estimates.

Table 1. Sediment-Trap-Derived Annual Flux to Depth Ratesa
RegionTrap IDCollection, Interval, YearsLatitudeLongitudeWater Depth, mTrap Depth, mPOC Flux, mg m−2 d−1Trap TypeReference
  • a

    MIZ, marginal ice zone; SMT, Salzgitter Electronics, Kiel; OSU, Oregon State University; ACC, Antarctic Circumpolar Current; APFZ, Antarctic Polar Frontal Zone; and SAF, Subantarctic Front.

  • b

    Data used in regional comparisons.

  • c

    Sample time periods less than 1 year.

  • d

    Trap deployments less than an entire year: July–October (110 days), may be overestimated.

  • e

    Trap deployments less than an entire year: March–November (200 days), may be overestimated.

  • f

    Trap deployments less than an entire year: November–February (98 days), may be underestimated.

  • g

    Trap deployments less than an entire year: September–November (61 days), may be underestimated.

  • h

    POC calculated as 50% of the total particulate carbon reported based on simultaneous inorganic and organic carbon determinations of sediment trap material from the North Pacific [Wong et al., 1999].

  • i

    Trap deployments less than an entire year: August–December (112 days), may be underestimated.

  • j

    Trap deployments less than an entire year: November–April (170 days), may be underestimated.

  • k

    Trap deployments less than an entire year: November–August (276 days), may be overestimated.

  • l

    Trap deployments less than an entire year: January–November (304 days), may be underestimated.

  • m

    Trap deployments less than an entire year: May–December (200 days), may be underestimated.

  • n

    POC estimated assuming that the lower trap has the same combustible flux %C as the upper trap [Fischer et al., 2000; Wefer et al., 1988].

Polar Arctic
Subarctic AtlanticbLB-11983–198469.510316127611.37Parflux 5Honjo et al. [1987]
Subarctic AtlanticbBI-11984–1985761128002.85Parflux 5Honjo et al. [1987]
Subarctic AtlanticbFS-11984–198578.91.4282324420.41Parflux 6Honjo et al. [1987]
Subarctic AtlanticbSP11987–198878.96.71618108713.7Kiel SMTHebbeln [2000]
Subarctic AtlanticbSP21988–198978.96.7166111109.0Kiel SMTHebbeln [2000]
Subarctic AtlanticbSP31989–199078.96.71676112521.1Kiel SMTHebbeln [2000]
Subarctic AtlanticbNA-11985–198665.51305826300.59Parflux 6Honjo et al. [1987]
Norwegian Seab1986–198767.85.513005006.66funnelBathmann et al. [1990]
Subarctic AtlanticbNB-11985–198670−2326927490.53Parflux 6Honjo et al. [1987]
Greenland SeabOG1988–198972.5−9.5270050010.4KielBodungen et al. [1995]
Greenland SeabOG1988–198972.5−9.5270010003.56KielBodungen et al. [1995]
Greenland SeabOG1988–198972.5−9.5270022000.9KielBodungen et al. [1995]
Greenland SeabOG1989–199072.5−9.5270050010.1KielBodungen et al. [1995]
Greenland SeabOG1989–199072.5−9.5270010003.86KielBodungen et al. [1995]
Greenland SeabOG1990–199172.5−9.527005002.93KielBodungen et al. [1995]
Greenland SeabOG1990–199172.5−9.5270010002.05KielBodungen et al. [1995]
Greenland SeabOG1990–199172.5−9.5270022000.99KielBodungen et al. [1995]
Greenland SeabGB-211985–198674.6−6.7258819660.94Parflux 5Honjo et al. [1987]
Greenland SeabGB-231985–198675.6−6.7344528230.4Parflux 5Honjo et al. [1987]
 
Atlantic Ocean
NE Atlanticb1989–199047.8−19.5455531005.5Parflux 7Newton et al. [1994]
NABEbS1989–199033.8−21510011602.74Parflux 7Honjo and Manganini [1993]
NABEbS1989–199033.8−21510019802.82Parflux 7Honjo and Manganini [1993]
NABEbS1989–199033.8−21510044802.36Parflux 7Honjo and Manganini [1993]
NABEbN1989–199047.7−21.7443511104.05Parflux 7Honjo and Manganini [1993]
NABEbN1989–199047.7−21.7443521103.78Parflux 7Honjo and Manganini [1993]
NABEbN1989–199047.7−21.7443537302.74Parflux 7Honjo and Manganini [1993]
Sargasso SeabS21977c31.5−55.955819762.43dParfluxHonjo [1980]
Sargasso SeabS21977c31.5−55.9558136940.087dParfluxHonjo [1980]
Sargasso SeabS21977c31.5−55.9558152060.07dParfluxHonjo [1980]
Sargasso Sea/BATSBATS1988–199831.7−64.2440015026.0MultiPITBATS online data
Sargasso Sea/BATSBATS1989–199831.7−64.2440020020.2MultiPITBATS online data
Sargasso Sea/BATSbBATS1989–199831.7−64.2440030014.1MultiPITBATS online data
Sargasso Sea/BATSbBATS1989–199031.8−64.2440040012.2MultiPITBATS online data
Sargasso SeabSCIFF1979–198531.8−64.2440032002.0ParfluxDeuser et al. [1990]
SW AfricaNU2−291376818.9Usbeck [1999]
SW AfricaNU2-l1992–1993−28.614.6305525164.4Fischer et al. [2000]
SW AfricaWR11988–1989−20.19.22217164016.7Kiel SMTWefer and Fischer [1993]
SW AfricaWR2u1989–1990−209.2219659914Kiel SMTWefer and Fischer [1993]
SW AfricaWR2l1989–1990−209.22196165410.4Kiel SMTWefer and Fischer [1993]
SW AfricaWR31990–1991−209220816487.73Kiel SMTUsbeck [1999]
NW AfricabCV1u, 2u1992–199411.5−21496810007.36Kiel SMTUsbeck [1999]
NW AfricabCV1l, 2l1992–199411.5−21496845003.48Kiel SMTUsbeck [1999]
NW AfricabCB1-l1988–198920.8−19.7364621953.3Parflux 6Fischer et al. [1996]
NW AfricabCB2-l1989–199021.1−20.7409235024.4Parflux 5Fischer et al. [1996]
NW AfricabCB3-u1990–199121.1−20.740947305.5Kiel SMTFischer et al. [1996]
NW AfricabCB3-l1990–199121.1−20.7409435574.7Kiel SMTFischer et al. [1996]
NW AfricabCB4-u1991c21.1−20.741087339.3eKiel SMTFischer et al. [1996]
NW AfricabCB4-l1991c21.1−20.7410835625.5eKiel SMTFischer et al. [1996]
Equatorial AtlanticWA3u1993–1994−7.5−28.055706712.6Fischer et al. [2000]
Equatorial AtlanticWA3l−8−28557050310.81Usbeck [1999]
Equatorial AtlanticEA8u1991–1992c−5.8−9.434505987.45Usbeck [1999]
Equatorial AtlanticEA8m1991–1992c−5.8−9.4345018336.47Usbeck [1999]
Equatorial AtlanticEA8l1991–1992c−5.8−9.4345028903.92Usbeck [1999]
Equatorial AtlanticWA4u−4−268085.1Usbeck [1999]
Equatorial AtlanticWA4l−4−2645552.67Usbeck [1999]
Equatorial AtlanticGBZ41989–1990−2.2−9.939126963Kiel SMTWefer and Fischer [1993]
Equatorial AtlanticGBZ5u−2−105978.22Usbeck [1999]
Equatorial AtlanticGBZ5l−2−1033826.3Usbeck [1999]
Equatorial AtlanticGBN3u1989–19901.8−11.144818538.2Kiel SMTWefer and Fischer [1993]
Equatorial AtlanticGBN3l1989–19901.8−11.1448139216Kiel SMTWefer and Fischer [1993]
Subtropical AtlanticE1977–1978c13.5−5452883896.73fParflux 2Honjo [1980]
Subtropical AtlanticE1977–1978c13.5−5452889883.94fParflux 2Honjo [1980]
Subtropical AtlanticE1977–1978c13.5−54528837551.73fParflux 2Honjo [1980]
Subtropical AtlanticE1977–1978c13.5−54528850681.7fParflux 2Honjo [1980]
 
Pacific Ocean
Ocean Station POSP1989–199350−145425020018.2Parflux 5–7Wong et al. [1999]
Ocean Station PbOSP1983–199350−145425010007.42Parflux 5–7Wong et al. [1999]
Ocean Station PbOSP1982–199350−145425038003.10Parflux 5–7Wong et al. [1999]
Subarctic PacificbAleutian Islands49−174540048003.4Takahashi [1995]
Subarctic PacificbAleutian Islands49−174540048005.1Takahashi [1995]
Subarctic PacificbBering Sea53.5−177380032008.1Takahashi [1995]
Subarctic PacificbBering Sea53.5−1773800320010.5Takahashi [1995]
North central Pacific GyrebP11978c15.4−15257923783.56gParflux 2Honjo [1980]
North central Pacific GyrebP11978c15.4−15257929780.55gParflux 2Honjo [1980]
North central Pacific GyrebP11978c15.4−152579227781.09gParflux 2Honjo [1980]
North central Pacific GyrebP11978c15.4−152579242800.88gParflux 2Honjo [1980]
North central Pacific GyrebP11978c15.4−152579255820.66gParflux 2Honjo [1980]
North central Pacific Gyre/HOTALOHA1988–199922.8−158.0480015014hMultiPITHOT online data
North central Pacific Gyre/HOTALOHA1994–199622.8−158.048002009hMultiPITHOT online data
North central Pacific Gyre/HOTALOHA1988–199522.8−158.048003007.7hMultiPITHOT online data
North central Pacific Gyre/HOTbALOHA1989–199522.8−158.048005005.5hMultiPITHOT online data
South China SeabSCS-C1990–199514.6115.1431012004.20Parflux 6Jianfang et al. [1998]; Wiesner et al. [1996]
South China SeabSCS-C1990–199514.6115.1431022403.51Parflux 6Jianfang et al. [1998]
South China SeabSCS-C1990–199514.6115.1431037702.52Parflux 6Jianfang et al. [1998]; Wiesner et al. [1996]
South China SeabSCS-N1987–198818.5116375010003.92Parflux 6Jianfang et al. [1998]; Wiesner et al. [1996]
South China SeabSCS-N1987–198818.5116375033502.02Parflux 6Jianfang et al. [1998]; Wiesner et al. [1996]
North Equatorial CurrentNEC-T1988–198912.0134.3530012000.38Parflux 6Kempe and Knaack [1996]
North Equatorial CurrentNEC-B1988–198912.0134.3530043000.43Parflux 6Kempe and Knaack [1996]
Equatorial Counter CurrentECC-T1988–19895.0138.8413011301.78Parflux 6Kempe and Knaack [1996]
Equatorial Counter CurrentECC-B1988–19895.0138.8413031300.67Parflux 6Kempe and Knaack [1996]
Equatorial PacificbS1983–198411−1914048007003.12OSU trapDymond and Collier [1988]
Equatorial PacificbS1983–198411−140480016002.38OSU trapDymond and Collier [1988]
Equatorial PacificbS1983–198411−140480034001.62OSU trapDymond and Collier [1988]
Equatorial Pacificb9N1992–19939−140510021501.51ParfluxHonjo et al. [1995]
Equatorial Pacificb9N1992–19939−140510022501.52ParfluxHonjo et al. [1995]
Equatorial Pacificb9N1992–19939−140510044000.96ParfluxHonjo et al. [1995]
Equatorial Pacificb5N1992–19935−140449311916.02ParfluxHonjo et al. [1995]
Equatorial Pacificb5N1992–19935−140449320914.50ParfluxHonjo et al. [1995]
Equatorial Pacificb5N1992–19935−140449337933.84ParfluxHonjo et al. [1995]
Equatorial Pacificb2N1992–19932−140439722033.96ParfluxHonjo et al. [1995]
Equatorial PacificbC1983–19841−139440010952.96OSU trapDymond and Collier [1988]
Equatorial PacificbC1983–19841−139440018954.25OSU trapDymond and Collier [1988]
Equatorial PacificbC1983–19841−139440034953.26OSU trapDymond and Collier [1988]
Equatorial PacificbC1984–19851−139440010835.36OSU trapDymond and Collier [1988]
Equatorial PacificbC1984–19851−139440018836.78OSU trapDymond and Collier [1988]
Equatorial PacificbC1984–19851−139440029085.18OSU trapDymond and Collier [1988]
Equatorial PacificbEQ1992–19930−14043588804.64ParfluxHonjo et al. [1995]
Equatorial PacificbEQ1992–19930−140435822844.49ParfluxHonjo et al. [1995]
Equatorial PacificbEQ1992–19930−140435836184.38ParfluxHonjo et al. [1995]
Equatorial Pacificb2S1992–1993−2−140429335933.61ParfluxHonjo et al. [1995]
Equatorial Pacificb5S1992–1993−5−140419812162.72ParfluxHonjo et al. [1995]
Equatorial Pacificb5S1992–1993−5−140419820992.72ParfluxHonjo et al. [1995]
Equatorial Pacificb5S1992–1993−5−140419823162.80ParfluxHonjo et al. [1995]
Equatorial Pacificb12S1992–1993−12−135429412921.52ParfluxHonjo et al. [1995]
Equatorial Pacificb12S1992–1993−12−135429435940.72ParfluxHonjo et al. [1995]
Peru-Chile CurrentCH-3–41993–1994−30−73.2436023237.67Kiel SMTHebbeln et al. [2000]
Panama BasinbPB1979c5.35−81.9385666712.6iParfluxHonjo et al. [1982]
Panama BasinbPB1979c5.35−81.9385612688.95iParfluxHonjo et al. [1982]
Panama BasinbPB1979c5.35−81.9385622659.06iParfluxHonjo et al. [1982]
Panama BasinbPB1979c5.35−81.93856286910.9iParfluxHonjo et al. [1982]
Panama BasinbPB1979c5.35−81.93856376911.4iParfluxHonjo et al. [1982]
Panama BasinbPB1979c5.35−81.93856379110.6iParfluxHonjo et al. [1982]
Panama Basinb1979–19805.37−85.638608909.7Parflux 2Honjo [1982]
Panama Basinb1979–19805.37−85.63860259010.9Parflux 2Honjo [1982]
Panama Basinb1979–19805.37−85.63860356013.7Parflux 2Honjo [1982]
 
Indian Ocean
Arabian Sea, oceanicbMS51994–1995c106544118005.7jParflux 7Honjo et al. [1999]
Arabian Sea, oceanicbMS51994–19951065441123633.8Parflux 7Honjo et al. [1999]
Arabian Sea, oceanicbMS51994–19951065441139153.3Parflux 7Honjo et al. [1999]
Arabian Sea, oceanicbCAST198714.564.6390429133.0Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbCAST198614.564.6390629075.2Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbCAST198814.564.6390830217.1Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbEAST198915.668.6380729386.0Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbEAST198715.668.6377627723.8Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbEAST198615.668.6377627767.7Parflux 6Haake et al. [1993]
Arabian Sea, oceanicbEAST199015.668.6386229285.2Parflux 6Haake et al. [1993]
Arabian Sea, coastalbMS11994–199517.758.9144880810.5Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS11994–1995c17.758.9144899910.5kParflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS21994–199517.458.8365082813.5Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS21994–199517.458.8365090317.2Parflux 7Haake et al. [1993]
Arabian Sea, coastalbMS21994–199517.458.83650197417.4Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS21994–199517.458.83650314113.2Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS31994–199517.259.6347076413.2Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS31994–199517.259.6347085817.5Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS31994–199517.259.63470185716.3Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS31994–199517.259.63470287112.8Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS41994–199515.361.539808218.9Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS41994–199515.361.53980222911.1Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbMS41994–199515.361.5398034788.9Parflux 7Honjo et al. [1999]
Arabian Sea, coastalbWAST198616.360.3402430237.1Parflux 6Haake et al. [1993]
Arabian Sea, coastalbWAST198716.360.3402430366.9Parflux 6Haake et al. [1993]
Arabian Sea, coastalbWAST198816.360.3402430349.0Parflux 6Haake et al. [1993]
Arabian Sea, coastalbWAST199016.360.34024301612.3Parflux 6Haake et al. [1993]
Bay of BengalSouth-s1987–19884.487.3401710406.49ParfluxIttekkot et al. [1991]
Bay of BengalSouth-d1987–19884.487.3401730065.59ParfluxIttekkot et al. [1991]
Bay of BengalCentral-s1987–198813.284.432599067.23ParfluxIttekkot et al. [1991]
Bay of BengalCentral-d1987–198813.284.4325922827.15ParfluxIttekkot et al. [1991]
Bay of BengalNorth-s1987–198817.489.622638099.84ParfluxIttekkot et al. [1991]
Bay of BengalNorth-d1987–198817.489.6226317277.26ParfluxIttekkot et al. [1991]
 
Polar Antarctic
ACC, AtlanticbVIII-u1992−62.1−40.6328024536.62ParfluxPudsey and King [1997]
ACC, AtlanticbVIII-l1992−62.1−40.6328032592.81ParfluxPudsey and King [1997]
ACC, AtlanticbI-l1990−63.2−42.7379837772.07ParfluxPudsey and King [1997]
ACC, AtlanticbI-u1992−63.2−42.7379329666.53ParfluxPudsey and King [1997]
ACC, AtlanticbI-11992–63.2–42.7379337661.52ParfluxPudsey and King [1997]
ACC, AtlanticbII-l1990−63.5−41.7455245315.73ParfluxPudsey and King [1997]
ACC, AtlanticbIII-u1990−64−40.9453737105.11ParfluxPudsey and King [1997]
ACC, AtlanticWS2-l1987c−64.9−2.5500044560.47lParfluxWefer and Fischer [1991]
ACC, AtlanticbWS3-u1988–1989−64.9−2.550533606.47Fischer et al. [2000]
Bouvert IslandbBO1-u1990–1991−54.3−3.427344507.37funnelFischer et al. [2000]
Bouvert IslandBO2-u1987c−54.3−3.429654561.32mfunnelFischer et al. [2000]
Polar FrontbPF1-u1987–1988−50.1−5.937507008.93Fischer et al. [2000]
Polar FrontbPF3-u1989–1990−50.1−5.9378561410.5Fischer et al. [2000]
MIZ, AtlanticKG1-u1983–1984−62.3−57.519524945.56Parflux 6Fischer et al. [2000]
MIZ, AtlanticKG2-u1984–1985−62.3−57.516506930.99Parflux 6Fischer et al. [2000]
MIZ, AtlanticKG3-u1985–1986−62.3−57.519926873.07Parflux 6Fischer et al. [2000]
MIZ, AtlanticKG1-l1983–1984−61.3−57.5195215881.6nfunnelWefer et al. [1988]
MIZ, PacificMS51996–1997−66.2−17030169375.21Parflux 6Honjo et al. [2000]
ACC, PacificMS41996–1997−63.1−170288610316.03Parflux 6Honjo et al. [2000]
APFZ, PacificMS31996–1997−60.3−170395811036.3Parflux 6Honjo et al. [2000]
SAF, PacificMS21996–1998−56.9−17049249824.66Parflux 6Honjo et al. [2000]
SAF, PacificMS21996–1998−56.9−170492442241.71Parflux 6US JGOFS online data
SAF, PacificMS11996–1997−53.0−17554419861.1Parflux 6Honjo et al. [2000]

[14] The analytical determination of POC in sediment trap samples has been refined during the past few decades. Not all data sources (Table 1) specify the methodology used to separate particulate inorganic carbon (PIC) from POC. When methods are cited, both fuming with acid and acid rinsing are most commonly used to remove PIC. These methods may lead to the overestimations and underestimations of POC concentrations [Grasshoff et al., 1999]. Conversely, the treatment method used to remove PIC may be within the error of sediment trap sample processing [Honjo, 1980]. While the lack of methodological consistency introduces uncertainty into the comparison of sediment trap records, this problem, as well as other trap technology uncertainties, would have also been present in the data underlying the development of the Martin et al. [1987] and Suess [1980] parameterizations.

[15] To standardize analysis between regions where the frequency of sediment trap measurements at different depths varies, formulations of new flux to depth equations incorporate data binned between depth ranges. The flux estimates at each locale are averaged within the following depth ranges: 0.5 to 1 km, 1 to 2 km, 2 to 3 km, 3 to 4 km, and >4 km. Average flux values are assigned a nominal depth of the mean depth of observations in each depth range.

3.3. Estimating Primary Production and Export

[16] Table 2 includes regional estimates of primary production and export primarily obtained during JGOFS process, time series, and other field-based studies. In most cases, primary production was equated to net photosynthesis as estimated by 14C uptake experiments. The one exception is the Southern Ocean/Atlantic sector region. Here, primary production is estimated using an algorithm based on monthly climatological phytoplankton concentrations from the coastal zone color scanner (CZCS) and in situ 14C-based primary productivity data from throughout the Southern Ocean [Arrigo et al., 1998]. We made this exception because of the lack of 14C-based primary production results for this region.

Table 2. Regional Estimates of Primary Production and Particulate Organic Carbon (POC) Export From the Base to the Photic Zonea
RegionLatitudeLongitudeZ0, mf RatioExport, mg C m−2 d−1Primary Production, mg C m−2 d−1Reference: ExportReference: Primary Production
  • a

    Export rates derived from POC/234Th uptake experiments. Primary production estimates derived from 14C uptake incubation experiments.

  • b

    Derived from f ratios (assuming that export equals primary production times f ratio).

  • c

    Suggested annual mean (Table 2).

  • d

    Monthly weighted average April–August, 32°–50°N, 20°W data compilation (Tables 6 and 7; references cited within), may be overestimated.

  • e

    Derived from nutrient mass balances.

  • f

    Average March–October, may be overestimated.

  • g

    Annual average 1989–1993.

  • h

    Suggested annual mean.

  • i

    Winter, may be underestimated.

  • j

    Average April–July, may be overestimated.

  • k

    Average NE Monsoon, Spring Intermonsoon, Mid-SW Monsoon, and Late-SW Monsoon periods.

  • l

    Average February–March and August–September (Table 5).

  • m

    Average summer and winter (Table 9).

  • n

    Derived from regional remote sensing.

  • o

    Average November–March, 55°–65°S, 170°W (Table 4), export may be overestimated.

  • p

    Annual average Weddell Sea sector, pelagic and marginal ice zone (MIZ) (Table 2).

  • q

    Average coastal upwelling, may be underestimated [Jewell, 1994].

  • r

    Average March–May, may be underestimated [see Minas et al., 1986].

Greenland and Norwegian Seas65° to 79°−10° to 11°500.370b240Bodungen et al. [1995]cBodungen et al. [1995]c
NE Atlantic/NABE34° to 48°−21° to −22°400.45280b700Bury et al. [2001]dBury et al. [2001]d
Sargasso Sea/BATS32°−56° to −64°14030, 44e360Buesseler [1998]f; Michaels et al. [1994]e,gMichaels et al. [1994]g
Subarctic Pacific/OSP50°−145°70701000Charette et al. [1999]hBoyd and Harrison [1999]h
North Central Pacific gyre/HOT15° to 23°−151° to −158°15066e460Emerson et al. [1997]hKarl et al. [1996]h
South China Sea15° to 18°115° to 116°100230420Huang et al. [1996]iHuang [1988]j
Arabian Sea, oceanic10° to 16°65° to 69°90701000Buesseler et al. [1998] (stations n11, s11, and s15)kBarber et al. [2001] (stations n11, s11, and s15)k
Arabian Sea, coastal16° to 18°59° to 62°651301250Buesseler et al. [1998] (stations s2, s3, s4, and s7)kBarber et al. [2001] (stations s2, s3, s4, and s7)k
Equatorial Pacific (±2° latitude)−2° to 2°−139° to −140°114901035Murray et al. [1996] (stations 6–10)lMurray et al. [1996] (stations 6–10)l
Equatorial Pacific (±5° latitude)5°, −5°−137° to −140°13076780Murray et al. [1996] (stations 4 and 12)lMurray et al. [1996] (stations 4 and 12)l
Equatorial Pacific (±9°–16° latitude)9° to 16°, −9° to −16°−134° to −152°13042344Murray et al. [1996] (stations 1, 2, and 15)lMurray et al. [1996] (stations 1, 2, and 15)l
Panama Basin−82° to −86°700.43100b230Bishop et al. [1986]mBishop et al. [1986]m
Southern Ocean/Atlantic sector−50° to −65°−2° to −43°400.1560b380nSambrotto and Mace [2000]oArrigo et al. [1998]p
NW Africa12° to 21°−20° to −21°500.61200b2000Jewell [1994]q; Minas et al. [1986]qHuntsman and Barber [1977]r

[17] Estimates of primary production based on 14C uptake experiments, as in the case of sediment traps, may include errors. Estimates of primary production may differ significantly if they are derived from carbon fixed in POC or in both dissolved organic carbon (DOC) and POC [Sakshaug et al., 1997]. The duration of the incubation experiment is another potential source of error. Long incubation times may yield lower carbon uptake rates than short incubations (∼1 hour) because of the likelihood of the recycling of labeled carbon [Dring and Jewson, 1982; Sakshaug et al., 1997]. The organic C to chlorophyll a ratio is highly variable and is another potential source of error [Sakshaug et al., 1997]. Hence 14C-based estimates of primary production may include significant uncertainties.

[18] We employ several approaches to estimate export of particulate organic carbon from surface waters on regional and annual scales: 234Th, mass balances, and new production (Table 2). The 234Th-based export estimates use 234Th activity measurements to calculate vertical 234Th fluxes, which are multiplied by the organic C to 234Th ratio of sinking particulate material to quantify POC export. While this approach has been applied to a wide range of oceanographic settings [Buesseler, 1998] and is a preferred methodology [Buesseler, 1991], associated errors have not been quantified. Calculating the 234Th flux involves biases and uncertainties including steady state effects, time variability, and transport terms [Buesseler et al., 1992; Wei and Murray, 1992; Lee et al., 1993; Kim et al., 1999]. Additionally, estimates of the export of organic components are associated with large errors because of uncertainty in the ratio of C:234Th on sinking particles [Michaels et al., 1994; VanderLoeff et al., 1997; Gardner, 2000]. Careful elemental mass balances relying on annual budgets of dissolved and particulate material may offer the most accurate estimates of export and are incorporated where available.

[19] The export of organic carbon from surface waters is often estimated using f ratios by equating new production with export, assuming steady state on an annual basis. The f ratio is the ratio of new production to total (new plus regenerated) production. We apply this approach where annual 234Th and mass balance export estimates are unavailable. A significant and variable portion of total export calculated by this method may be in the form of DOC [e.g., Quay, 1997; Stoll et al., 1996] and unsuitable for comparison to the POC flux recorded by sediment traps. At high latitudes, where DOC is a minor component of flux and 234Th-based export rates are available during only a few months, rates of POC export are derived by assuming that new production equals POC export.

4. Results and Discussion

4.1. Flux to Depth

[20] A review of the locations of annual sediment trap sites reveals large areas with little or no data (Figure 1). The Northern Hemisphere contains almost 3 times the number of flux to depth estimates as the Southern Hemisphere contains, despite having less than 40% of the global ocean area. Few sediment trap data are available from the western sides of main ocean basins. The central ocean gyres and large portions of the Southern Ocean are poorly characterized. Areas of low productivity are relatively undersampled compared to more productive coastal margins. Oligotrophic and eutrophic portions of the ocean are relatively undersampled, compared to mesotrophic areas (70% of total samples). Furthermore, the moderately productive Southern Hemisphere Subtropical Convergence (∼40°S) has received little attention. Globally, the bulk of flux to depth data is from depths greater than 1 km.

[21] Annual carbon flux to depth for all global locations is shown in Figure 2. Above 1 km, global variability of annual flux to depth is more than an order of magnitude larger than below that depth (Table 3). In the intermediate and deep ocean, variability decreases with increasing depth. Here, the vertical flux of POC follows an irregular pattern of both increasing and decreasing flux with increasing depth (Table 4). In almost half of the POC flux rate change estimates the flux to deeper traps exceeds the flux observed in shallower traps in the same region. The irregular pattern may be due to a variable availability of sinking material to decomposition, differential particle sinking trajectories [Siegel et al., 1990; Siegel and Deuser, 1997], trapping inaccuracies, or heterogeneity of particle production and export and flux to depth within the regions considered. The variability of flux to depth estimates in the intermediate and deep ocean constitutes a minor fraction of particle production and export. Most of the modification of flux to depth occurs in the upper 1 km of the water column.

Table 3. Descriptive Statistics of Flux Rates at Different Depth Ranges in the Global Oceana
Depth, kmAverageStandard DeviationMinimumMaximumN
  • a

    Flux rates are given in units of mg C m−2 d−1.

0.1–0.2517.56.49.026.05
0.25–0.57.23.61.314.114
0.5–17.44.70.5518.940
1–26.85.40.3821.130
2–34.53.30.4012.838
3–45.43.70.0913.738
>42.01.70.075.715
Table 4. Average Rate of Change of the Vertical POC Flux to Depth in the Intermediate and Deep Ocean Derived From Sediment Trap Dataa
 Percent Δ Flux km−1
1–2 km2–3 km>3 km
  • a

    Positive and negative values indicate the percent by which flux observed in deeper traps exceeds or lags flux at shallower traps within the depth ranges indicated.

  • b

    Average over 1 to 3 km range.

  • c

    Average over 2 to >3 km range.

Greenland and Norwegian Seas−7976
NE Atlantic/NABE−3.163−54
Sargasso Sea/BATS−79b−79b−61
Subarctic Pacific/OSP12b12b−46
North Central Pacific gyre/HOT5555−16
South China Sea−12−3860
Arabian Sea, oceanic68−39
Arabian Sea, coastal41−32
Equatorial Pacific (±2° latitude)177.642
Equatorial Pacific (±5° latitude)−249c9c
Equatorial Pacific (±9°–16° latitude)−29−17c−17c
Panama Basin1.2439.8
Southern Ocean, Atlantic sector−45−39
NW Africa−4635−30

[22] Where flux data are available for both the shallow and deep ocean, fluxes to depths between 0.5 and 1 km are highly correlated with fluxes to depths greater than 1 km (Figure 3). In contrast to Yu et al. [2001] and Scholten et al. [2001], these correlations suggest that sediment trap data from depths between 0.5 to 1 km may be as “valid” as those from below 1 km. The variability of upper ocean fluxes indicates that the conditions and forcings that serve to create and attenuate variability in flux to depth are concentrated within 1 km below the base of the photic zone. While sediment-trap-derived flux to depth data may be internally consistent, primary production and export are poorly correlated with flux (Table 5). This lack of correlation suggests that using primary production or export alone may not allow for accurate predictions of flux to depth.

Figure 3.

Relationships between sediment-trap-derived POC flux to depth estimates within different depth ranges for regions listed in Table 2.

Table 5. Correlation Matrix for Primary Production, Export From the Base of the Photic Zone (Table 2), and Flux to Various Depth Ranges (Table 1)
 Primary ProductionExportFlux (0.5–1 km)Flux (1–2 km)Flux (2–3 km)Flux (3–4 km)Flux (>4 km)
Primary production1      
Export0.741     
Flux (0.5–1 km)0.160.251    
Flux (1–2 km)0.030.320.931   
Flux (2–3 km)−0.100.150.850.791  
Flux (3–4 km)0.020.200.910.780.871 
Flux (>4 km)0.410.620.990.950.780.911

4.2. Predicted Versus Observed Flux to Depth

[23] We compare observed flux to depth, derived from sediment trap data, to predicted flux to depth using the flux algorithms of Suess [1980] and Martin et al. [1987] derived from primary production and export beneath the base of the euphotic zone, respectively (Figure 4). Both the Suess [1980] and Martin et al. [1987] relationships describe flux as decreasing more rapidly with depth in the upper ocean and less rapidly with depth in the deep ocean. Disagreement between predicted and observed flux to depth is generally greatest in regions where export and primary production are larger. Disagreement is also larger in the shallow subphotic ocean (0.1–2 km) and approaches observed values with increasing depth. Within this depth range, overall disagreement is typically largest with the Suess [1980] relationship, which overestimates observed flux to depth by an average of 8 times and a maximum of 36 times. Here, the Martin et al. [1987] relationship overestimates observed flux by an average of 6 times and a maximum of 23 times. Worldwide, the Suess [1980] and Martin et al. [1987] relationships both overestimate and underestimate flux to the deep ocean (>1.5 km). The Suess [1980] and Martin et al. [1987] relationships predict flux to the deep ocean by factors ranging from 0.2 to 6 (3.1 average) and from 0.4 to 14 (3.3 average) times observed values, respectively.

Figure 4.

Regional observed (solid circles; Table 1) and radiochemically corrected (open circles) sediment-trap-based flux to depth, export (diamonds; Table 2), and primary production (squares; Table 2). Regional empirical algorithms describing the observed flux of particulate organic carbon to depth (equations (8), solid black line, and (9), dashed black line) are compared to those of Martin et al. [1987] (solid red line) and Suess [1980] (dashed red line).

[24] The Martin et al. [1987] relationship predicts observed flux to depth well in some regions (Arabian Sea, Southern Ocean/Atlantic sector, and subarctic Pacific/OSP) and overestimates flux to depth in other regions studied. In regions with export values >200 mg C m−2 d−2 (NW Africa, South China Sea NE, and Atlantic/NABE), disagreement is larger. Here, predictions range between 5 and 14 times the observed values, increasing with increasing export. These disagreements suggest that organic carbon flux varies less with depth in the deep ocean than predicted by the Martin et al. [1987] relationship. Furthermore, in all regions, the use of the Martin et al. [1987] relationship with a variable exponent (instead of a fixed −0.858) underestimates observed flux to depths greater than 2 km. This implies that the use of a power law equation to describe flux to depth may overestimate the rate of change of flux with depth in the deep ocean. The inaccuracy of flux to depth exhibited by the Martin et al. [1987] and Suess [1980] relationships is probably due, in part, to the refinement of POC export and primary production methodologies over the past two decades.

4.3. Storage Efficiency p and s Ratios

[25] In order to compare flux of organic carbon between ocean regions, flux to depth is normalized to local primary production and export:

equation image
equation image

The p and s ratios describe the vertical transport of organic carbon normalized relative to surface water primary production and export, respectively (Figure 5). These ratios gauge the efficiency of the retention of sinking organic carbon, the storage efficiency, within the deep ocean.

Figure 5.

Observed flux to depth normalized to (a) primary production (p ratio: flux/primary production) and (b) export (s ratio: flux/export) for the major time series, JGOFS, and other oceanographic studies.

[26] In general, different ocean regions exhibit different groupings of p and s ratios. These groupings are more easily distinguished with s ratios than with p ratios. Large storage efficiencies of exported carbon (s ratios) are found in the Panama Basin, subarctic Pacific/OSP, Arabian Sea, and Southern Ocean/Atlantic sector, regions. The NW Africa, north central Pacific gyre/HOT, NE Atlantic/NABE, and South China Sea regions commonly exhibit low exported carbon storage efficiencies. Fluxes per unit of carbon produced during primary production (p ratios) are largest in the Panama Basin, Southern Ocean/Atlantic sector, and Arabian Sea regions. Smaller storage efficiencies of carbon derived from primary production are found in the NW Africa, north central Pacific gyre/HOT, and NE Atlantic/NABE regions. Worldwide, the fraction of carbon fluxed to the deep ocean (>1.5 km) ranges from 0.10 to 8.8% (1.1% average) of primary production and from 0.28 to 30% (5.7% average) of export.

[27] There is little direct relationship between primary production and export and corresponding p and s ratios. Correlations between primary production or export and the regional p and s ratios are poor (all r2 < 0.5). Overall, p and s ratios tend to be larger at regions with larger rates of primary production and export, suggesting that flux to depth may be more efficient during periods of low primary production and export.

4.4. Regional Empirical Algorithms

[28] The flux of POM to depth is mediated by complex physical and biological interactions that are not well understood. These interactions control the depth-dependent rates of POM sinking and remineralization. In order to better relate flux to depth to the relevant controls, we propose describing flux to depth using a minimum of parameters that include sinking and remineralization rates. Thus, flux to depth (z) can be described by the exponential equation:

equation image

where D is the instantaneous rate of decay and W is the sinking rate, both in the same units of time [Banse, 1990, 1994].

[29] POM fluxing to depth is composed of many individual particles with a continuum of individual decay and sinking rates. As POM sinks, labile organic fractions are remineralized rapidly, allowing refractory material to become more important with depth [Asper and Smith, 1999; Bishop, 1989]. We recognize both labile and refractory fractions of sinking POM and approximate this process by modifying (5) to describe flux as the sum of two fractions of POM (s1 and s2), with decay rates (D1 and D2) and sinking rates (W1 and W2) normalized to export (equation (4)):

equation image

We rely on several assumptions to minimize the number of parameters needed to describe this process. Flux to depth typically decreases rapidly with increasing depth in the upper ocean. The magnitude of change of flux with increasing depth is greatly diminished in the deep ocean relative to the upper ocean. We assume that the rapid upper ocean decrease of flux to depth constitutes the rapid decay of fresh labile organic material and the near-constant fluxes approached in the deep ocean correspond to rapidly sinking organic material and/or the refractive resistance organic material to regeneration. Hence we approximate flux to depth where a fraction of POM sinks quickly or remineralizes slowly enough that decay is essentially zero (when D2 approaches zero or W2 approaches infinity) and (6) reduces to

equation image

For simplicity, we define ks = (D1 / W1) m−1 and rewrite (7):

equation image

Equation (8) describes the relationship between export and flux to depth in various oceanographic regions. To describe the relationship between primary production and flux to depth, we substitute the p ratio (equation (3)) for the s ratio in (6), (7), and (8), yielding

equation image

The parameter kp is defined in a similar manner to ks. Limitations of this approximation of the flux to depth process include decay and sinking rates, which change with depth (i.e., a variable k with depth). This approximation may be insensitive to gradual decreases in the rate of flux with increasing depth, as observed in the deep ocean [Martin et al., 1987; Suess, 1980]. The use of constant depth-independent terms (p2 and s2) is based on our regional analysis, which indicates that flux in the deep ocean increases with depth almost as often as it decreases with depth (Table 2).

[30] The results of the exponential fits of (8) and (9) applied to observed and radiochemically corrected regional sediment-trap-derived flux to depth, export, and primary production rate estimates are described in Tables 6a and 6b and Figures 4 and 6. These equations typically predict flux to the deep ocean within 20% of the average observed values. The p2 and s2 parameters describe the more rapidly sinking and/or more refractive portions of flux to the deep ocean and sediment surface. These parameters generally approximate minimum p and s ratios. The p2 refractive/rapidly sinking fractions of primary production are above average in the Panama Basin and Southern Ocean/Atlantic sector regions. The s2 refractive/rapidly sinking portions of export are above average in the Panama Basin, Southern Ocean/Atlantic sector, Subarctic Pacific/OSP, and Arabian Sea regions. The p2 and s2 values indicate that from 0.21 to 4.9% (1.2% average) of primary production and from 0.37 to 11% (4.6% average) of export reaches the deep ocean (>1.5 km), similar to calculated p and s ratios.

Figure 6.

Regional profiles of (a and b) observed and (c and d) radiochemically corrected POC flux to depth normalized to primary production (PP) and export below the photic zone (equations (1), (2), (8), and (9); Tables 6a and 6b) for the upper 2000 m depth. Regions shown include the following: 1, Greenland and Norwegian Seas; 2, NE Atlantic/NABE; 3, Sargasso Sea/BATS; 4, Subarctic Pacific/OSP; 5, north central Pacific gyre/HOT; 6, South China Sea; 7, Arabian Sea (regional average); 8, equatorial Pacific (regional average); 9, Panama Basin; 10, Southern Ocean, Atlantic sector; and 11, NW Africa. Profiles and model results derived from the Suess [1980] and Martin et al. [1987] relationships are included for comparison (lines 12 and 13 (thick lines), respectively).

Table 6a. Regional Empirical Parameters Describing Particulate Organic Carbon Flux to Depth Normalized to Primary Production Using Unadjusted and Radiochemical Calibrated Sediment Trap Fluxesa
 ObservedRadiochemical Calibration
p11/kp, mp2p11/kp, mp2
  • a

    See text. The e-folding length scale of remineralization is given by 1/kp. All r2 values are >0.93, except for the Greenland and Norwegian Seas region. Equation: p(z) = image + p2.

Greenland and Norwegian Seas1.531160.004401.005500.00104
NE Atlantic/NABE1.371250.004851.192230.00481
Sargasso Sea/BATS1.832210.02983.891020.00617
Subarctic Pacific/OSP10.829.40.006275.8039.70.00813
North central Pacific gyre/HOT61.436.40.0021021.748.80.00259
South China Sea1.881570.006881.532300.00779
Arabian Sea (regional average)1.891190.007471.521810.00744
Equatorial Pacific (regional average)3.201070.004373.211050.0109
Panama Basin1.691220.04631.431700.0491
Southern Ocean, Atlantic sector1.9956.80.01481.7370.40.0172
NW Africa1.611040.002381.441360.00301
Table 6b. Regional Empirical Parameters Describing Particulate Organic Carbon Flux to Depth Normalized to Export Using Unadjusted and Radiochemical Calibrated Sediment Trap Fluxesa
RegionObservedRadiochemical Calibration
s11/ks, ms2s11/ks, ms2
  • a

    See text. The e-folding length scale of remineralization is given by 1/ks. All r2 values are >0.93, except for the Greenland and Norwegian Seas region. Equation: s(z) = image + s2.

Greenland and Norwegian Seas1.281780.01451.005290.00398
NE Atlantic/NABE1.321370.01211.142750.0119
Sargasso Sea/BATS6.5574.10.003721.325990.0112
Subarctic Pacific/OSP2.2477.60.08961.004390.0939
North central Pacific gyre/HOT8.1570.90.01323.091220.0149
South China Sea1.741770.01241.422780.0135
Arabian Sea (regional average)1.401830.08131.104550.0617
Equatorial Pacific (regional average)2.021670.04431.532430.0832
Panama Basin1.441460.1011.212280.112
Southern Ocean, Atlantic sector1.331050.09041.151670.0938
NW Africa1.551170.003931.381530.00487

[31] The p1, s1, 1/kp, and 1/ks parameters describe the more labile and/or more slowly sinking portion of flux. Together they approximate the remineralization length scale, or e-folding depth of flux. Smaller p1 and s1 values decrease the portion of flux entering the ocean at depth z0. Larger 1/kp and 1/ks values deepen the inflection point of the curve describing flux, below which flux approaches p2 or s2 values and becomes constant with depth. The net effect is to diminish the supply of carbon to the upper ocean.

[32] These parameters are poorly constrained because of a lack of and potential unreliability of flux data in the mesopelagic zone. Parameterizations are highly sensitive to whether or not upper ocean sediment trap data are deemed valid. Applying the radiochemical correction generally lowers p1 and s1 values and increases 1/kp and 1/ks values, with the net result of decreasing flux to depth in the upper ocean. In this case, parameters derived may be considered to estimate maximum flux to depth. For both the observed and radiochemically corrected flux data, values for p2 and s2 greater than 0.01 are only found where primary production and export are less than 400 mg C m−2 d−1 and 150 mg C m−2 d−1, respectively. These results suggest that where primary production and export are low, a greater portion of the transported material is refractory and/or rapidly sinking.

4.5. Effect on Carbon Storage

[33] We performed a set of simulations in a one-dimensional ocean model to assess the influence of the various remineralization profiles (equations (1), (2), (8), and (9); Tables 6a and 6b) on the retention of CO2 generated by the remineralization of POC below the photic zone. We allowed a pulse of POC to remineralize in the ocean interior according to each regional profile and simulated how long it would take for the ΣCO2 generated at depth to be transported back up to the photic zone.

[34] The ocean model used here is described by Caldeira et al. [1998]. The ocean is represented by a box diffusion model [Oeschger et al., 1975; Siegenthaler, 1983], which is essentially a one-dimensional column representing mean oceanic vertical transport. We make no attempt to simulate regional differences in ocean circulation. The diffusion coefficients for the vertical transport of dissolved matter vary with depth. The diffusion coefficients were chosen [Caldeira et al., 1998] such that the change in ocean 14CO2 inventory between 1945 and 1975 matches the estimated 1975 bomb radiocarbon inventory [Broecker et al., 1995] of 305 × 1026 atoms and the modeled 1975 ocean mean and surface ocean Δ14CO2 matches the basin-volume-weighted mean of the natural plus bomb Δ14CO2 values measured in the Geochemical Ocean Sections Study (GEOSECS) program [Broecker et al., 1985]. The Δ14C is a normalized and 13C-adjusted 14C/12C ratio, and δ13C is a normalized 13C/12C ratio [Broecker and Peng, 1982]. This tuning yields a vertical eddy diffusion coefficient of 8820 m2 yr−1 at the base of the mixed layer diminishing with an e-folding length scale of 500 m to a minimum of 2910 m2 yr−1 at the ocean bottom. Similar parameter values were used in previous simulations [Oeschger et al., 1975; Siegenthaler, 1983; Hesshaimer et al., 1994].

[35] Analysis using this one-dimensional ocean model indicates that the residence time of biogenic carbon may vary up to 2 orders of magnitude depending on the regional location of carbon fixation and export. The Suess [1980] and Martin et al. [1987] relationships both yield residence times similar to the maximum of regional relationships derived in this study (Figure 7). Parameters derived from the radiochemically corrected flux to depth data typically yield longer residence times than the observed flux to depth data. Simulations based on regional profiles indicate that the residence time of POC exported below the euphotic zone in the deep ocean may span 2 orders of magnitude.

Figure 7.

Predictions of (a and b) observed and (c and d) radiochemically corrected carbon storage below the photic zone using a one-dimensional ocean model (see text). Regions shown include the following: 1, Greenland and Norwegian Seas; 2, NE Atlantic/NABE; 3, Sargasso Sea/BATS; 4, Subarctic Pacific/OSP; 5, north central Pacific gyre/HOT; 6, South China Sea; 7, Arabian Sea (regional average); 8, equatorial Pacific (regional average); 9, Panama Basin; 10, Southern Ocean, Atlantic sector; and 11, NW Africa. Profiles and model results derived from the Suess [1980] and Martin et al. [1987] relationships are included for comparison (lines 12 and 13 (thick lines), respectively).

5. Conclusions

[36] We demonstrate that the commonly applied Martin et al. [1987] and Suess [1980] relationships approximate flux to depth in several locations. However, these relationships overestimate flux to depth in most ocean regions. The overestimation of flux to depth is more pronounced with the Suess [1980] equation. Our observations indicate that these constant power law and rational relationships used in current large-scale oceanographic models generally overestimate deepwater POC fluxes and hence underestimate particle regeneration in the water column. For a given ocean circulation model, the use of these relationships could result in unreliable estimates of new production and residence time of exported carbon in the deep ocean.

[37] We illustrate regional variability in the biological pump’s ability to store carbon in the ocean below the photic zone. Flux to depth normalized to primary production and export indicates from 0.1 to 8.8% (1.1% average) of primary production and from 0.28 to 30% (5.7% average) of export enters the deep ocean (>1.5 km). The use of new region-specific empirical flux to depth algorithms, which in part parameterize the lability of settling particulate organic matter, in a one-dimensional ocean model suggests up to 2 orders of magnitude of variability in the efficiency of carbon storage in the ocean. Applying a radiochemical correction to the observed POC flux to depth tends to lengthen remineralization length scales and subsequently increase the predicted residence time of carbon in the ocean. Global relationships between primary production and export out of the euphotic zone and flux to depth remain unclear.

[38] From our analysis it is not clear that export is any more directly related to flux to depth than is primary production. Consideration of other processes which modify the efficiency of the biological pump may improve this relationship. Modifications to the sinking flux include zooplankton swimming and excretion at depth [Bishop, 1989; Bishop et al., 1986; Vinogradov, 1970], the association of fluxing material with hard parts and mineral surfaces [Ittekkot et al., 1991; Lee et al., 1999], variability of the mixed layer depth [Fischer et al., 1996], mass sedimentation events [DiTullio et al., 2000; Kemp et al., 2000; Smetacek, 2000], plankton community structure [Boyd and Newton, 1999], primary production seasonality [Berger and Wefer, 1990; Lampitt and Antia, 1997], the rate of microbial decomposition [Arnosti et al., 1998; Cho and Azam, 1988; Laws et al., 2000], and non-Redfield uptake of nutrients and decomposition of organic matter [Arrigo et al., 1999; Pahlow and Riebesell, 2000].

Acknowledgments

[39] We thank the following researchers for their inspiration and advice: James Bishop (Laurence Berkeley National Laboratory), Kevin Arrigo (Stanford University), and Donald Olson (RSMAS, University of Miami). This research was conducted as a portion of M. Lutz’s Ph.D. dissertation and was supported by a number of sources, including the NSF ROAVERRS program, DOE Center for Research on Ocean Carbon Sequestration, Stanford University McGee Foundation, and International JGOFS Program (Ocean Biogeochemical Modeling Course, Bangalore, India).

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