Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Funding

These data were collected from a variety of different publications and methods. The shared features of these datasets is that all samples reflect dissolved (e.g. filtered) samples, though the filter types and pore sizes varied from study to study. Treatment and sample preparation varied from study to study as well. None of the data in this compilation represents original measurements. 

No additional processing occurred beyond compiling the datasets from their original publications.

* Added publications from dataset under related publications
* adjusted parameter names to comply with database requirements

NSF Award Abstract:
Nearly all of the photosynthesis in the oceans is carried out by microscopic, single-cell “plants” called phytoplankton. The photosynthesis by phytoplankton forms the base of the food chain, supporting almost all life in the oceans. One of the key nutrients that phytoplankton need to grow is iron, which is often in short supply in ocean surface waters and can limit the phytoplankton growth and photosynthesis rates. This project seeks to better understand the cycling of iron in the oceans, focusing on the removal of iron from the oceans by particle scavenging. Particle scavenging refers to dissolved iron sticking to large, sinking particles, which ultimately remove iron to the sediments. This modeling study will simulate iron cycling in the oceans, along with the cycling of several different metal isotopes, that are also subject to removal by particles scavenging, but do not act as nutrients for phytoplankton. This will help separate the biological influences on iron distributions, from the impacts of particle scavenging and other physical processes. The external sources of iron to the oceans coming from dust deposition, ocean sediments, river runoff, and the seafloor hydrothermal vents will also be evaluated. This work is important for understanding how climate change and human activities will modify the iron cycle and impact biogeochemistry in the future. This project will also support two graduate students and an undergraduate student researcher.

The model simulations will be evaluated and constrained with extensive comparisons to field measurements of iron and the other key variables. The GEOTRACES program has recently produced a global set of ship measurement surveys, with full depth measures of numerous isotopes and trace elements, including iron, that are ideal for evaluating the prognostic ocean model (Community Earth System Model (CESM) ocean component). The GEOTRACES datasets are also ideal for incorporation into our offline, inverse model (OCIM, CYCLOCIM) which can interpret the still sparse observations in the context of 3D circulation and biogeochemistry. The simulations of 230Th, 232Th, 231Pa, and Fe cycling will improve mechanistic understanding of particle scavenging and place stronger observational constraints on the patterns and magnitude of external lithogenic sources of trace elements to the oceans. Results and products from this study, with the ocean model component of the Community Earth System Model (CESM), will be incorporated into future versions of CESM, to improve the current ability to predict how ocean biogeochemistry and marine ecosystems will respond to climate change along a range of potential future climate trajectories.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.