Acronym: OCB-036
Program: Ocean Carbon & Biogeochemistry [OCB]
Url: Project Web Site
Start date: 2007-9
End date: 2010-8
Geolocation: Global
Description:

from the NSF proposal abstract

Remineralization ratios represent the average stoichiometric relationships of elements released by decomposition of sinking particles as they fall thought the water column to the ocean floor. In theory, these ratios are similar, on appropriate temporal and spatial scales, to the ratios in which elements are taken up by phytoplankton. These ratios are often used in biogeochemical modeling and they permit linking the different cycles through simple proportionality. Although variations in the ratio in space or time can have large-scale oceanic impact, current consensus suggests that remineralization ratios are relatively constant in the deep ocean, but that significant variations exist in the more dynamic upper layers. If one is to correctly predict the impacts of iron fertilization, to measure the efficiency of the organic carbon pump, or to investigate the effects of climate change on oceanic biogeochemical cycles, and so make claims about the significance of these processes on anthropogenically relevant scales (decades), an accurate global depiction of organic matter remineralization is required. Researchers from Princeton University propose to carry out a global investigation of the pattern of water column remineralization of carbon, alkalinity, oxygen and the major nutrients (nitrate, phosphate, silicate) using a newly developed mathematical estimation scheme and the Global Ocean Data Analysis Project (GLODAP) data set. Using a newly developed method to solve a coupled system of equation describing mixing of multiple water masses and remineralization of particulate matter into dissolved nutrients, they can simultaneously solve for the water mass fractions and each remineralization ratio, without assuming ratio constancy, and propagate uncertainties in water mass characterization using a geographic Monte-Carlo approach.

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More information about project Stoichiometry of Oceanic Remineralization by Non-Linear Global Optimization on an Improved Data Set
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