Primary productivity and particle fluxes on a transect of the equator at 153°W in the Pacific Ocean

Betzer, Peter R.; Showers, William J.; Laws, Edward A.; Winn, Christopher D.; DiTullio, Giacomo R.; Kroopnick, Peter M.

doi:10.1016/0198-0149(84)90068-2

Cited by 397 publications

(146 citation statements)

References 27 publications

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“…Considering all the assumptions used above, the calculated number should be considered a first-order estimate of lateral flux. Additionally, we show that the Betzer et al (1984) formula for calculation of carbon flux seems to work also for the Arctic Ocean.…”

Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

“…1; Stein et al, 2001. Based on the accumulation rates of total organic carbon, which includes the marine as well as the terrigenous proportion (Stein et al, 2001), and the microscopical investigations of the organic carbon composition (maceral data show that 25% of the carbon is marine; Boucsein and Stein, 2000), only 0.4% of the Table 7 Basics and results from the calculation of the proportion of lateral terrigenous organic carbon flux and lateral lithogenic matter flux including data from (a) Stein et al (2001), (b) Boucsein and Stein (2000), (c) calculated according to Betzer et al (1984) with primary production of 18 g C m À2 y À1 after Boetius and Damm (1998), and (e) . Betzer et al (1984 (Table 7).…”

Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

“…This results in a lateral transport of lithogenic material of 65%. Second, using the primary production according to Boetius and Damm (1998), the depth-dependent degradation of marine organic carbon after Betzer et al (1984), and the measured POC flux in the trap (Table 7), we calculate the terrigenous organic carbon proportion. At the shallow trap, we do not know the exact amount of lateral transport.…”

Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

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Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Fahl

Nöthig

2007

Deep Sea Research Part I: Oceanographic Research Papers

108

107

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Investigations of lithogenic and biogenic particle fluxes using long-term sediment traps are still very rare in the northern high latitudes and are restricted to the arctic marginal seas and sub-arctic regions. Here data on the variability of fluxes of lithogenic matter, CaCO 3 , opal, and organic carbon and biomarker composition from the central Arctic Ocean are presented for a 1-year period. The study was carried out on material obtained from a long-term mooring system equipped with two multi-sampling traps, at 150 and 1550 m depth, and deployed on the southern Lomonosov Ridge close to the Laptev Sea continental margin from September 1995 to August 1996. In addition, data from surface sediments were included in the study. Annual fluxes of lithogenic matter, CaCO 3 , opal, and particulate organic carbon were 3.9, 0.8, 2.6, and 1.5 g m À2 y À1 , respectively, in the shallow trap and 11.3, 0.5, 2.9, and 1.05 g m À2 y À1 , respectively, in the deep trap.Both the shallow and the deep trap showed significant variations in vertical flux over the year. Higher values were found from mid-July to the end of October (total mass flux of 75-130 mg m À2 d À1 in the shallow trap and 40-225 mg m À2 d À1 in the deep trap). During all other months, fluxes were fairly low in both traps (most total mass flux values o10 mg m À2 d À1 ). The interval of increased fluxes can be separated into (1) a mid-July/August maximum caused by increased primary production as documented in high abundances of marine biomarkers and diatoms and (2) a September/October maximum caused by increased influence of Lena River discharge indicated by maximum lithogenic flux and large amounts of terrigenous/fluvial biomarkers in both traps. During September/October, total mass fluxes in the deep trap were significantly higher than in the shallow trap, suggesting a lateral sediment flux at greater depth. The lithogenic flux data also support the importance of sediment input from the Laptev Sea for the sediment accumulation on the Lomonosov Ridge on geological time scales, as indicated in sedimentary records from this region. r

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Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

Section: Source and Transport Of The Lithogenic Mattermentioning

confidence: 99%

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Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Fahl

Nöthig

2007

Deep Sea Research Part I: Oceanographic Research Papers

108

107

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“…His model, as well as other subsequent ones (e.g. Betzer et al 1984;Berger et al 1987;Pace et al 1987), predicts the particle flux J z at a given depth (z in meters), as a function of depth and the surface primary production (P ) through the expression (Suess 1980):…”

Section: Inferences Of Organic Matter Mineralization From Carbon Fluxesmentioning

confidence: 99%

“…POC fluxes measured from deep-sea (bathypelagic) moored sediment traps have been used to derive empirical models which predict the vertical profile of POC flux in the whole water column, by relating it to primary production and depth (Suess 1980;Betzer et al 1984;Berger et al 1987;Pace et al 1987;Lohrenzen et al 1992;Antia et al 2001). In this way, the export particulate production may be estimated from the POC flux at the base of the euphotic zone/mixed layer.…”

Section: Delivery Of Pocmentioning

confidence: 99%

Respiration in the mesopelagic and bathypelagic zones of the oceans

Arı́stegui¹,

Agustı́²,

Middelburg³

et al. 2005

Respiration in Aquatic Ecosystems

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OutlineIn this chapter the mechanisms of transport and remineralization of organic matter in the dark water-column and sediments of the oceans are reviewed. We compare the different approaches to estimate respiration rates, and discuss the discrepancies obtained by the different methodologies. Finally, a respiratory carbon budget is produced for the dark ocean, which includes vertical and lateral fluxes of organic matter. In spite of the uncertainties inherent in the different approaches to estimate carbon fluxes and oxygen consumption in the dark ocean, estimates vary only by a factor of 1.5. Overall, direct measurements of respiration, as well as indirect approaches, converge to suggest a total dark ocean respiration of 1.5-1.7 Pmol C a −1 . Carbon mass balances in the dark ocean suggest that the dark ocean receives 1.5-1.6 Pmol C a −1 , similar to the estimated respiration, of which >70% is in the form of sinking particles. Almost all the organic matter (∼92%) is remineralized in the water column, the burial in sediments accounts for <1%. Mesopelagic (150-1000 m) respiration accounts for ∼70% of dark ocean respiration, with average integrated rates of 3-4 mol C m −2 a −1 , 6-8 times greater than in the bathypelagic zone (∼0.5 mol C m −2 a −1 ). The results presented here renders respiration in the dark ocean a major component of the carbon flux in the biosphere, and should promote research in the dark ocean, with the aim of better constraining the role of the biological pump in the removal and storage of atmospheric carbon dioxide.

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Satellite estimates of net community production based on O₂/Ar observations and comparison to other estimates

Cassar

2016

Global Biogeochemical Cycles

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We present two statistical algorithms for predicting global oceanic net community production (NCP) from satellite observations. To calibrate these two algorithms, we compiled a large data set of in situ O2/Ar‐NCP and remotely sensed observations, including sea surface temperature (SST), net primary production (NPP), phytoplankton size composition, and inherent optical properties. The first algorithm is based on genetic programming (GP) which simultaneously searches for the optimal form and coefficients of NCP equations. We find that several GP solutions are consistent with NPP and SST being strong predictors of NCP. The second algorithm uses support vector regression (SVR) to optimize a numerical relationship between O2/Ar‐NCP measurements and satellite observations. Both statistical algorithms can predict NCP relatively well, with a coefficient of determination (R2) of 0.68 for GP and 0.72 for SVR, which is comparable to other algorithms in the literature. However, our new algorithms predict more spatially uniform annual NCP distribution for the world's oceans and higher annual NCP values in the Southern Ocean and the five oligotrophic gyres.

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Primary productivity and particle fluxes on a transect of the equator at 153°W in the Pacific Ocean

Cited by 397 publications

References 27 publications

Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Respiration in the mesopelagic and bathypelagic zones of the oceans

Satellite estimates of net community production based on O₂/Ar observations and comparison to other estimates

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Primary productivity and particle fluxes on a transect of the equator at 153°W in the Pacific Ocean

Cited by 397 publications

References 27 publications

Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Lithogenic and biogenic particle fluxes on the Lomonosov Ridge (central Arctic Ocean) and their relevance for sediment accumulation: Vertical vs. lateral transport

Respiration in the mesopelagic and bathypelagic zones of the oceans

Satellite estimates of net community production based on O2/Ar observations and comparison to other estimates

Contact Info

Product

Resources

About

Satellite estimates of net community production based on O₂/Ar observations and comparison to other estimates