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Evaluating the Effects of High Particulate Fluxes on Chemical Processes Occurring at the Amazone River Ocean Boundary

Evaluating the Effects of High Particulate Fluxes on Chemical Processes Occurring at the Amazone River Ocean Boundary
评估高颗粒通量对亚马逊河海洋边界发生的化学过程的影响
批准号:
9116974
负责人:
David Nelson
金额:
$6.15万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1992
资助国家:
美国
项目状态:
已结题
起止时间:
1992-01-01 至 1994-12-31

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中文摘要
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英文摘要
This proposal is a renewal for the existing grant entitled "Evaluating the Effects of High Particulate Fluxes at the Amazon River/Ocean Boundary," which is part of the AmasSeds (A Multi- Disciplinary Amazon Shelf SEDiment Study) Project. Three research cruises to the Amazon shelf (August 1989; February, 1990; May 1990; and November, 1991) have been completed successfully. This time series approach to understanding the chemical, physical, and geological processes active at the Amazon River/ocean boundary enables the investigators to resolve the variable influences of river discharge, tidal resuspension, local wind stress, and the intensity of coastal currents on particle-associated processes. The specific topics of research described in this proposal include: 1) evaluating the effects of suspended sediment concentration on the biological uptake and regeneration of nutrients and carbon; 2) the release of radium isotopes to the water column from particles and sediments and their use in tracking seabed/water column exchange processes; 3) scavenging of particle-reactive elements from continental shelf waters; 4) uranium cycling during river/ocean mixing; and 5) tracing biological and physical processes on the Amazon shelf based on the distribution of carbon and stable isotopic data. Measurements of radioactive tracers in the water column and seabed enable investigators to characterize many of these processes on a variety of time scales (ranging from days to hundreds of years). This proposal requests support for two additional years of research, which will be used to complete data analyses, work up individual data sets, model the initial results, and integrate the field measurements with the other research groups taking part in the project.
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