BEGIN:VCALENDAR
VERSION:2.0
PRODID:Baylor CMS Calendar /PHP/
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:US_Central
BEGIN:STANDARD
DTSTART:20001029T020000
RRULE:FREQ=YEARLY;WKST=MO;INTERVAL=1;BYMONTH=11;BYDAY=1SU
TZNAME:Standard Time
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20010401T020000
RRULE:FREQ=YEARLY;WKST=MO;INTERVAL=1;BYMONTH=3;BYDAY=2SU
TZNAME:Daylight Saving Time
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:Baylor_CMS_Event-79359
DTSTAMP:20130524T122643Z
SUMMARY:Geo 5050 Colloquium Series: Dr. Steve Driese, Baylor University
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:Construction of a Fully Searchable Soils Database Integrating Soil Characterization Data and Whole-Soil Geochemical Data=0D=0A=
Paleopedological studies rely heavily on the use of contemporary soil characterization and whole-soil geochemical data [1, 2, 3].  These soil science resources serve the needs of paleopedologists who reconstruct ancient climate and soil systems using models to relate modern physical/chemical soil characterization data, whole-soil geochemical data, and climate parameters [3, 4, 5, 6]. The (paleo)pedologist currently faces a “data overload” problem due to a number of global and continental-based soil geochemical databases becoming widely available. The overwhelming nature of the available data makes model construction difficult and time-consuming. The emerging field of data analytics addresses the overload problem by providing a systematic process for data acquisition, cleaning, initial analysis and main analysis. We used a data analytics approach to construct the Baylor Paleosol Informatics Cloud (BU-PIC).  The BU-PIC uniquely combines: (1) USDA-NRCS pedon data, (2) PRISM-based climate parameters, (3) NLCD land-cover attributes, and (4) published paleosol data. This aggregation of data will allow paleopedologists to upload standardized geochemical data and test and refine soil-derived paleoclimate proxies and paleopedotransfer functions.  Although BU-PIC development is in the initial stages of data cleaning, preliminary analysis shows promising results. For example, variations in whole-soil weight % Fe2O3 explain approximately 76% of the variance in % Fed (pedogenic iron) in all soil horizons spanning 4000 pedons, and variations in whole-soil weight % CaO explain approximately 86% of the variance in CaCO3% in 865 pedons (A and B horizons only, no gypsum). This may be useful for paleopedologists interested in determining the amount of pedogenic iron and pedogenic carbonate within a lithified paleosol. Binning by specific soil orders and soil textural classes suggests that proxies can be improved by separation rather than aggregation seeking “universal” proxies. We believe the success of BU-PIC will rely on building rapport with modern soil scientists while seeking their consultation during the developmental stages. [1] Sheldon, Retallack & Tanaka (2002), Journal of Geology 110, 687-696. [2] Driese et al. (2005) Journal of Sedimentary Research 75, 339-349. [3] Nordt & Driese (2010), Geology 38, 407-410. [4] Nordt & Driese (2010), American Journal of Science 310, 37-64. [5] Nordt, Dworkin & Ashley (2011) GSA Bulletin 123, 1745-1762. [6] Nordt et al. (2012) Geochimica et Cosmochimica Acta 87, 267-282.
LOCATION:BSB E231
DTSTART;TZID=US_Central:20120928T150000
DTEND;TZID=US_Central:20120928T160000
END:VEVENT
END:VCALENDAR
