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.
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
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
GIS, Topography, Morphometry, Carbon, Biomass
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: Gordon Gulch - Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover (2010)." Retrieved 19 Jun 2019, from http://criticalzone.org/catalina-jemez/data/dataset/5138/
Department of Energy DE-SC0006968
National Science Foundation NSF-1331408
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).
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**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
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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.
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* 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.