Initial Publication Date: January 1, 2018

Quantifying Distributed Deformation near Oceanic Transform Faults: Examples from Cyprus and Iceland

Sarah J. Titus, Department of Geology, Carleton College
Chelsea Wagner, Department of Geology, Carleton College
William Chapman, Department of Geology, Carleton College
Joshua R. Davis, Department of Mathematics and Statistics, Carleton College
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To characterize distributed deformation near oceanic transform faults, we study two systems: the Arakapas fault exposed in the Troodos ophiolite, Cyprus, and the Husavik-Flatey fault in northern Iceland. Rocks in the ophiolite preserve patterns of deformation at mid-crustal levels whereas rocks in the active system in Iceland preserve evidence of deformation in the upper crust.

For both systems, we compile as much structural and paleomagnetic data as possible from our own measurements and from the literature. Our primary datasets are lava and dike directions and paleomagnetic directions from a variety of rock types. For paleomagnetic data, we work with in situ rather than tilt-corrected directions. We also work with as much data as possible, using means from individual lava flows rather than from stacks of lavas. These choices allow us to characterize the variability in the data sets without making assumptions about the relative timing of tilting versus deformation.

Our analysis of these datasets shows that distributed deformation is typically concentrated within 10 km of each transform fault with more limited deformation at greater distances from the fault. For Iceland, we use regressions to quantify fault-perpendicular gradients in the data, where multiple data sets indicate clockwise rotations of 4 to 5 degrees per kilometer over a 20-km-wide region. These rotations are about steeply plunging, but not vertical, axes. The rocks in Cyprus provide a view of fault-perpendicular and fault-parallel variations in datasets. Again, we use regressions of the structural and paleomagnetic data to quantify variation over space; these in turn can be interpreted as recording the temporal development of the system.

Session

Shear Zones