Dataset Listing

Como Creek - Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover (2010)

Topographic Carbon Storage

Variables:  X, Y, ID, UTME, UTMN, HT, PRED, AREA, EQDIAM, MAJAX, MINAX, MAXHT, MINHT, MEANHT, EVT_Boulder, xmin, xmax, ymin, ymax, sten_num, agc_sum, nrmht, slope, aspect, cata, planc, twi, vllydpth, tpi, slpht, genc, midslp, dem, stdht, profc

Date Range:  (2010-05-01 to 2010-05-01)

Dataset Creators/Authors:  Tyson Lee Swetnam, Paul Brooks, Holly Barnard, Adrian Harpold, Erika Gallo

Contact:  Tyson Lee Swetnam, University of Arizona, 1064 E Lowell St Tucson AZ 85721, tswetnam@email.arizona.edu

Field Area:  

Description
Keywords & XML
Citation
Publications
Acknowledgements
  • Description

    The 'Stems' data are from an individual tree segmentation (Swetnam and Falk 2014) derived from the 2010 snow-off lidar and biomass-carbon allometric equations. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

    The '10m Topo points' data are derived from a bare earth digital elevation model (DEM) generated from the 2010 snow-off lidar flight, these include the topographic metrics and the biomass-carbon for each pixel derived from the sum of STEMS. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

    A total of three catchments in Boulder Creek were analyzed: Como Creek, Gordon Gulch, and Betasso Preserve.

    Significance Statement:

    Forest carbon reservoirs in complex terrain along an elevation-climate gradient spanning an 11 Celsius range in mean annual temperature (MAT) and a 50 cm yr-1 range in mean annual precipitation (MAP) did not exhibit the expected response of increasing in size with greater MAP and idealized MAT. Within catchments, the distribution of mean and peak carbon storage doubled in size for valleys versus ridges. These results suggest spatial variations in carbon storage relate more to topographically mediated water availability, as well as aspect (energy-balance) and topographic curvature (a proxy for soil depth and depth to ground water), than elevation-climate gradients. Consequently, lateral redistribution of precipitation across topographic position may either moderate or exacerbate regional climatic controls over ecosystem productivity and tree-level responses during drought.
    Comments
    Description of the data production are given in the Supplemental Information in Swetnam et al. (in review) and are online at: Mapping aboveground biomass from individual tree segmentation data
  • Keywords

    GIS, Topography, Morphometry, Carbon, Biomass

    XML Metadata

    http://criticalzone.org/boulder/data/xml-metadata-test/5137/

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

  • Citation for This Dataset

    Swetnam and Falk, Application of metabolic scaling theory to reduce error in local maxima tree segmentation from aerial LiDAR, 2014, Forest Ecology and Management, 323, 158-167.

    Citation for This Webpage

    Tyson Lee Swetnam, Paul Brooks, Holly Barnard, Adrian Harpold, Erika Gallo (2010). "CZO Dataset: Como Creek - Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover (2010)." Retrieved 13 Dec 2017, from http://criticalzone.org/boulder/data/dataset/5137/

  • Publications

    Other Publications

    2014

    Application of Metabolic Scaling Theory to reduce error in local maxima tree segmentation from aerial LiDAR. Swetnam T.L. and Falk D.A. (2014): Forest Ecology and Management 323: 158–167

  • Acknowledgements

    Funding

    Department of Energy DE-SC0006968
    National Science Foundation NSF-1331408

Data

Como Creek - STEMS

(.csv)   Data Level 0,  Metadata

Como Creek - 10m Topo points

(.zip)   Data Level 0,  Metadata

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 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

    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 http://www.datacite.org/whycitedata.


CZO Field Areas

 


CZO Authors

Explore Further

data |

Explore Further