Shale and sandstone are the most common lithologies of the forested ridges throughout the Appalachian Mountains. The overall goal of this thesis was to determine whether these two rock types impart distinct biogeochemical properties to soils and plants. The effects of rock type (lithology) on soil gas concentration, nutrient concentration and nutrient limitation were studied in the Ridge and Valley province of central Pennsylvania. To increase understanding of lithological controls on soil gases (Chapter 1), we monitored the depth distribution of soil CO2 and O2 concentrations in central Pennsylvania in two watersheds on different lithologies. We deployed gas monitoring instrumentation on two catena transects that included four topographical positions, one located on sandstone and the other on shale. As expected, with increasing soil depth O2 concentrations decreased while pCO2 increased. CO2 and O2 concentrations varied more with topographical position than with lithology, as the valley floor positions in both catenas had the highest pCO2 for a given depth. Both manual sampling from gas access tubes throughout the soil profile and continuous sampling by buried sensors documented these patterns.
Soil Gas, CO2, O2, automated sensors, hand sampled, soil moisture, TDR
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
Jason Kaye; Lillian Hill (2016). "CZO Dataset: Garner Run and Shale Hills - Soil Gas, Soil Moisture (2015-2016)." Retrieved 24 Aug 2019, from http://criticalzone.org/shale-hills/data/dataset/6639/
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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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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.