This article is a non-peer reviewed preprint published at EarthArXiv. The article is in review by Geochimica et Cosmochimica Acta. 1 Statistics and segmentation: 2 Using Big Data to assess Cascades Arc compositional variability 3 Bradley W. Pitcher1 and Adam JR. Kent2 4 5 1Earth and Environmental Sciences department, Vanderbilt University, Nashville, TN 32701. 6 Email:
[email protected] 7 2College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97333. 8 Email:
[email protected] 9 10 11 Abstract 12 Primitive lavas erupted in the Cascades arc of western North America demonstrate significant 13 patterns of along-arc heterogeneity. Such compositional diversity may be the result of 14 differences in mantle melting processes, subduction geometry, regional tectonics, or 15 compositions of the slab, mantle or overlying lithosphere. Previous authors have partitioned the 16 arc into four geochemically distinct segments in order to assess the importance and relative roles 17 of these potential causes (Schmidt et al., 2008). However, despite the immense amount of data 18 available from the Cascade arc, no previous study has utilized a statistical approach on a 19 comprehensive dataset to address such a fundamental petrologic question. To better characterize 20 the heterogeneity of the entire arc, we compiled >250,000 isotopic, major, and trace element 21 analyses (glass and whole rock) from nearly 13,000 samples. To minimize inherent sampling 22 bias – the effect where well-studied volcanoes heavily weight conclusions – we use a weighted 23 bootstrap Monte Carlo approach in which the probability of a sample being selected to the 24 posterior distribution was inversely proportional to the number of samples within its 0.25° 25 latitude bin.