Soil samples analyzed via Mössbauer spectroscopy at three temperatures (295K, 77K and 4.2K). In each case the sample is loaded into the machine without prior modification (no grinding) to an ideal thickness based on the amount of iron in the sample. Transmission 57Fe Mössbauer spectroscopy was performed with a variable temperature He-cooled system with a 1024 channel detector. A 57Co source (~50 mCi) embedded in a Rh matrix was used at room temperature. Samples were mounted between two pieces of 0.127 mm thickness Kapton tape. In some cases, this was done inside an anoxic glovebox, and transferred immediately to the spectrometer cryostat to avoid sample oxidation prior to analysis. In other cases dried samples were used. The velocity (i.e., gamma-ray energy) was calibrated using α-Fe foil at 298 K. The transducer was operated in constant acceleration mode and folding was performed against the calibrated Fe foil to achieve a flat background. The raw sample files here are folded spectra using the most recent collected calibration standard. Data collection times are typically 24 h per sample per temperature, however can be longer/shorter in samples with less/more iron concentration.
Soil samples of enriched and depleted iron horizons were collected previously by Dan Richter and passed to Aaron Thompson in 2015. Each sample was previously air-dried. Dried samples were loaded into the Mössbauer spec. at the University of Georgia, located in Barrow Hall on the main Athens campus and each sample was analyzed for ~24h at three temperatures (295K, 77K and 4.2K). Samples from the upper two horizons did not have sufficient iron to collect quality spectrum.
Iron, soil, Calhoun
XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.
Citation for This Dataset
Aaron Thompson, Dan Richter, Jared Wilmoth, Diego Barcellos, 2015, Mössbauer spectroscopy of Enriched Fe horizon of Calhoun historic soil pits, http://criticalzone.org/calhoun/data/dataset/4678/
Citation for This Webpage
Aaron Thompson; Dan Richter; Jared Wilmoth; Diego Barcellos (2015). "CZO Dataset: Calhoun CZO - Soil Geochemistry (2015) - Mössbauer spectroscopy." Retrieved 18 Aug 2019, from http://criticalzone.org/national/data/dataset/4678/
Depth Variation of Soil Iron Crystallinity at the Calhoun Critical Zone Observatory. Thompson, A., Barcellos, D., Wilmoth, J., and Richter, D. (2015): Calhoun CZO 2015 Summer Science Meeting
Data Use Policy
1. Use our data freely. All CZO Data Products* except those labelled Private** are released to the public and may be freely copied, distributed, edited, remixed, and built upon under the condition that you give acknowledgement as described below. Non-CZO data products — like those produced by USGS or NOAA — have their own use policies, which should be followed.
2. Give proper citation and acknowledgement. Publications, models and data products that make use of these datasets must include proper citation and acknowledgement. Most importantly, provide a citation in a similar way as a journal article (i.e. author, title, year of publication, name of CZO “publisher”, edition or version, and URL or DOI access information. See http://www.datacite.org/whycitedata). Also include at least a brief acknowledgement such as: “Data were provided by the NSF-supported Southern Sierra Critical Zone Observatory” (replace with the appropriate observatory name).
3. Let us know how you will use the data. The dataset creators would appreciate hearing of any plans to use the dataset. Consider consultation or collaboration with dataset creators.
*CZO Data Products. Defined as a data collected with any monetary or logistical support from a CZO.
**Private. Most private data will be released to the public within 1-2 years, with some exceptionally challenging datasets up to 4 years. To inquire about potential earlier use, please contact us.
Data Sharing Policy
All CZO investigators and collaborators who receive material or logistical support from a CZO agree to:
1. Share data privately within 1 year. CZO investigators and collaborators agree to provide CZO Data Products* — including data files and metadata for raw, quality controlled and/or derived data — to CZO data managers within one year of collection of samples, in situ or experimental data. By default, data values will be held in a Private CZO Repository**, but metadata will be made public and will provide full attribution to the Dataset Creators†.
2. Release data to public within 2 years. CZO Dataset Creators will be encouraged after one year to release data for public access. Dataset Creators may chose to publish or release data sooner.
3. Request, in writing, data privacy up to 4 years. CZO PIs will review short written applications to extend data privacy beyond 2 years and up to 4 years from time of collection. Extensions beyond 3 years should not be the norm, and will be granted only for compelling cases.
4. Consult with creators of private CZO datasets prior to use. In order to enable the collaborative vision of the CZO program, data in private CZO repositories will be available to other investigators and collaborators within that CZO. Releasing or publishing any derivative of such private data without explicit consent from the dataset creators will be considered a serious scientific ethics violation.
* CZO Data Products. Defined as data collected with any monetary or logistical support from a CZO. Logistical support includes the use of any CZO sensors, sampling infrastructure, equipment, vehicles, or labor from a supported investigator, student or staff person. CZO Data Products can acknowledge multiple additional sources of support.
** Private CZO Repository. Defined as a password-protected directory on each CZO’s data server. Files will be accessible by all investigators and collaborators within the given CZO and logins will be maintained by that local CZO’s data managers. Although data values will not be accessible by the public or ingested into any central data system (i.e. CUAHSI HIS), metadata will be fully discoverable by the public. This provides the dual benefit of giving attribution and credit to dataset creators and the CZO in general, while maintaining protection of intellectual property while publications are pending.
† Dataset Creators. Defined as the people who are responsible for designing, collecting, analyzing and providing quality assurance for a dataset. The creators of a dataset are analogous to the authors of a publication, and datasets should be cited in an analogous manner following the emerging international guidelines described at http://www.datacite.org/whycitedata.
To fully zoom into a small area, you may need to visit the "Map" button and uncheck "Terrain" view.