Dataset Listing

Luquillo Mountains - Soil Redox Potential, Soil Biogeochemistry - Fe speciation, redox (2016-2018)

Contrasting Fe speciation in two humid forest soils: Insight into organomineral complexation in redox-active environments

Variables:  iron, ferric ion, ferrous ion

Standard Variables:  Iron

Date Range:  (2016-05-15 to 2018-04-21)

Dataset Creators/Authors:  Elizabeth K. Coward; Aaron Thompson; Alain F. Plante

Contact:  Miguel Leon,

Field Area:   Northeastern Puerto Rico and the Luquillo Mountains

Keywords & XML
  • Description

    While the contribution of iron (Fe)-bearing minerals to organic carbon (C) stabilization in terrestrial systems is well-described, the influence of Fe solid-phase speciation on organomineral associations is unclear in highly dynamic, oxidation-reduction (redox)-active soils. In humid tropic forest soils, fluctuations in redox state accelerate weathering of Fe-bearing mineral phases, producing a spectrum of mineral sizes and bonding environments available for C stabilization, and confounding our understanding of C stability. Characterizing these Fe-bearing phases can improve predictions of the response of redox-active soil systems to climatic changes that may alter Fe mineral crystallinity and solubility, such as precipitation intensity, storm event frequency and temperature. Leveraging inorganic selective dissolution techniques, 57Fe Mössbauer spectroscopy (MBS), specific surface area (SSA) analyses and X-ray diffraction (XRD), we investigated mineral speciation in surface soils of contrasting lithologies from the Luquillo Critical Zone Observatory (LCZO), Puerto Rico. The LCZO provides a model investigatory framework in which high C inputs to surface horizons by similar vegetation, topography and climatic forcings are intercepted by highly-weathered, volcaniclastic Oxisols or quartz diorite-derived Inceptisols, producing a gradient of Fe content and speciation. Strong correlations observed between Fe concentrations and extraction-induced changes in SSA indicated target Fe phases contribute substantially to SSA of the bulk mineral matrix. MBS analysis of untreated soils reveal both Oxisol and Inceptisol soils are largely composed of FeIII-oxyhydroxides, accompanied by substantial FeII and silicate FeIII contributions in Inceptisol soils. FeIII-oxyhydroxides in the Oxisol soils were largely short-range-ordered (SRO), and notably, a fraction of particularly low-crystallinity FeIII-oxyhydroxide mineral phases in these soils appear protected against harsh reductive dissolution, whereas the overall higher crystallinity Fe phases in the Inceptisol soils do not. These findings suggest that some high-SSA, SRO FeIII phases, which likely also have high C sorption capacities, may be immobilized against reduction in these Oxisol soils. Consequently, C associated with these FeIII phases may be preferentially stabilized in Oxisol soils, potentially driving disparate C mineralization and CO2 production rates across contrasting lithologies.
  • Keywords

    Fe oxides, Solid-phase speciation, C stabilization, Mössbauer spectroscopy

    XML Metadata

    XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.

  • Citation for This Dataset

    Elizabeth K.Coward, AaronThompson, Alain F.Plante (2018): Contrasting Fe speciation in two humid forest soils: Insight into organomineral associations in redox-active environments. Geochimica et Cosmochimica Acta. DOI: 10.1016/j.gca.2018.07.007

    Citation for This Webpage

    Elizabeth K. Coward; Aaron Thompson; Alain F. Plante (2018). "CZO Dataset: Luquillo Mountains - Soil Redox Potential, Soil Biogeochemistry (2016-2018) - Fe speciation, redox." Retrieved 31 Mar 2020, from

  • Publications

    Primary Publications


    Contrasting Fe speciation in two humid forest soils: Insight into organomineral associations in redox-active environments. Elizabeth K.Coward, AaronThompson, Alain F.Plante (2018): Geochimica et Cosmochimica Acta


Luquillo Mountains - Fe speciation, redox

(docx)   Data Level 2

Data Use Policy
Data Sharing Policy
  • Data Use Policy

    DRAFT v.0.4.0

    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 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

    DRAFT v.0.2.5

    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

Explore Further

data |

Explore Further