
New Late Permian paleomagnetic data from Argentina: Refinement of the apparent polar wander path of Gondwana
Author(s) -
Domeier Mathew,
Van der Voo Rob,
Tohver Eric,
Tomezzoli Renata N.,
Vizan Haroldo,
Torsvik Trond H.,
Kirshner Jordan
Publication year - 2011
Publication title -
geochemistry, geophysics, geosystems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.928
H-Index - 136
ISSN - 1525-2027
DOI - 10.1029/2011gc003616
Subject(s) - gondwana , paleomagnetism , geology , apparent polar wander , permian , paleontology , polar wander , path (computing) , geophysics , tectonics , structural basin , computer science , programming language
The Late Paleozoic–Early Mesozoic apparent polar wander path of Gondwana is largely constructed from relatively old paleomagnetic results, many of which are considered unreliable by modern standards. Paleomagnetic results derived from sedimentary sequences, which are generally poorly dated and prone to inclination shallowing, are especially common. Here we report the results of a joint paleomagnetic‐geochronologic study of a volcanic complex in central Argentina. U‐Pb dating of zircons has yielded a robust age estimate of 263.0 +1.6/−2.0 Ma for the complex. Paleomagnetic analysis has revealed a pretilting (primary Permian) magnetization with dual polarities. Rock magnetic experiments have identified pseudo‐single domain (titano)magnetite and hematite as the mineralogic carriers of the magnetization. Lightning‐induced isothermal remagnetizations are widespread in the low‐coercivity magnetic carriers. The resulting paleomagnetic pole is 80.1°S, 349.0°E, A 95 = 3.3°, N = 35, and it improves a Late Permian mean pole calculated from a filtered South American paleomagnetic data set. More broadly, this new, high‐quality, igneous‐based paleomagnetic pole falls between the previously distinct Late Permian segments of the Laurussian and Gondwanan apparent polar wander paths, suggesting that the long‐recognized disparity between these large paleomagnetic data sets may be primarily due to the inclusion of low‐quality or systemically biased data.