HR: 14:25h
AN: V33D-04    [Abstracts]
TI: A Chemistry-Based Classification for Peridotite Xenoliths
AU: * Block, K A
EM: kblock@ldeo.columbia.edu
AF: Lamont-Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, United States
AU: Ducea, M
EM: ducea@email.arizona.edu
AF: University of Arizona, Gould-Simpson Building #77, 1040 E 4th St., Tucson, AZ 85721, United States
AU: Raye, U
EM: uraye@utdallas.edu
AF: University of Texas at Dallas, 2601 North Floyd Road, Richardson, TX 75080, United States
AU: Stern, R J
EM: rjstern@utdallas.edu
AF: University of Texas at Dallas, 2601 North Floyd Road, Richardson, TX 75080, United States
AU: Anthony, E Y
EM: eanthony@utep.edu
AF: University of Texas at El Paso, Geological Sciences 321, El Paso, TX 79968, United States
AU: Lehnert, K A
EM: lehnert@ldeo.columbia.edu
AF: Lamont-Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, United States
AB: The development of a petrological and geochemical database for mantle xenoliths is important for interpreting EarthScope geophysical results. Interpretation of compositional characteristics of xenoliths requires a sound basis for comparing geochemical results, even when no petrographic modes are available. Peridotite xenoliths are generally classified on the basis of mineralogy (Streckeisen, 1973) derived from point-counting methods. Modal estimates, particularly on heterogeneous samples, are conducted using various methodologies and are therefore subject to large statistical error. Also, many studies simply do not report the modes. Other classifications for peridotite xenoliths based on host matrix or tectonic setting (cratonic vs. non-cratonic) are poorly defined and provide little information on where samples from transitional settings fit within a classification scheme (e.g., xenoliths from circum-cratonic locations). We present here a classification for peridotite xenoliths based on bulk rock major element chemistry, which is one of the most common types of data reported in the literature. A chemical dataset of over 1150 peridotite xenoliths is compiled from two online geochemistry databases, the EarthChem Deep Lithosphere Dataset and from GEOROC (http://www.earthchem.org), and is downloaded with the rock names reported in the original publications. Ternary plots of combinations of the SiO2- CaO-Al2O3-MgO (SCAM) components display sharp boundaries that define the dunite, harzburgite, lherzolite, or wehrlite-pyroxenite fields and provide a graphical basis for classification. In addition, for the CaO-Al2O3-MgO (CAM) diagram, a boundary between harzburgite and lherzolite at approximately 19% CaO is defined by a plot of over 160 abyssal peridotite compositions calculated from observed modes using the methods of Asimow (1999) and Baker and Beckett (1999). We anticipate that our SCAM classification is a first step in the development of a uniform basis for classifying mantle xenoliths and will facilitate the use of databases to model physical characteristics such as density and anisotropy for integration with geophysical measurements.
UR: http://www.earthchem.org
DE: 0525 Data management
DE: 0530 Data presentation and visualization
DE: 1038 Mantle processes (3621)
DE: 3621 Mantle processes (1038)
SC: Volcanology, Geochemistry, Petrology [V]
MN: 2007 Fall Meeting