Dataset Listing

Shale Hills, Garner Run (Sandstone Forested) - Vegetation (2015)

Level 1 - Quality Controlled Data

Variables:  Line (Transect Name; Starting point = first letter in transect name), Distance (m; along transect where the subplot was located), species label (4 letter species code for each shrub stem labeled with first two letters of Latin genus name followed by first two letters of Latin species name), diameter (cm; at root collar), dbh (cm; diameter at breast height where applicable)

Standard Variables:  Diameter at breast height (DBH)|Distance|Species

Date Range:  (2015-2015)

Dataset Creators/Authors:  Brubaker, Kristen

Contact:  Kristen Brubaker, Assistant Professor of Environmental Studies, Hobart and William Smith Colleges. 300 Pulteney St. Geneva, NY 14456 (315) 781-3445

Field Area:   Garner Run - Sandstone Forested | Susquehanna Shale Hills Critical Zone Observatory

Keywords & XML
  • Description

    We measured the root collar diameter and species of all shrubs present in sub-plots along the established vegetation transects at Shale Hills and Garner Run watersheds. Sub-plots were placed every 10 and 20 meters at Shale Hills and Garner Run, respectively. Each sub-plot was 2 m by 2 m square, centered on the tape. All stems between 0.1 cm and 10 cm at root collar diameter were measured using a caliper and identified by species. Species were coded by Latin name, with the first two letters of the genus and first two letters of the species.
  • Keywords

    Shrubs, understory, biomass

    XML Metadata

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

  • Citation for This Dataset

    The following acknowledgment should accompany any publication or citation of these data: Logistical support and/or data were provided by the NSF-supported Susquehanna Shale Hills Critical Zone Observatory.

    Citation for This Webpage

    Brubaker, Kristen (2015). "CZO Dataset: Shale Hills, Garner Run (Sandstone Forested) - Vegetation (2015)." Retrieved 25 Feb 2020, from


Shale Hills & Garner Run - Shrub Data - 2015

(xlsx)   Data Level 1,  Metadata,  [Private]

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

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