Statistics and segmentation: Using Big Data to assess Cascades arc compositional variability
Statistics and segmentation: Using Big Data to assess Cascades arc compositional variability
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DOI：
10.31223/osf.io/6xq3w
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发表时间：
2018-09
影响因子：
5
通讯作者：
B. Pitcher;A. Kent
中科院分区：
文献类型：
--
作者：
B. Pitcher;A. Kent
摘要北美西部喀斯喀特岛弧喷发的原始熔岩和镁铁质熔岩表现出沿弧不均匀性的显著模式。这种成分的多样性可能是地幔熔融过程、俯冲几何学、区域构造或板块、地幔或上覆岩石圈成分差异的结果。以前的作者已经将弧划分为四个地球化学上不同的部分，以评估这些过程的重要性和相对作用（施密特等人，2008年）。然而，尽管有大量的数据可从瀑布弧，没有以前的研究已经利用了一个全面的数据集，以解决弧分割及其成因的统计方法。为了更好地描述整个弧的不均匀性，我们首先从12，000多个样品中收集了超过235，000个同位素，主要和微量元素分析（玻璃和整个岩石），其成分范围从镁铁质到长英质，包括弧前和弧后中心的数据。我们专注于2236基性岩弧前样品在我们的汇编，以评估潜在的原因沿弧差异较小的岩浆，并可能减少地壳同化的任何影响。为了最大限度地减少固有的抽样偏差--研究充分的火山对结论的影响--我们使用加权自助蒙特卡罗方法，其中样本被选入后验分布的概率与其0.25°纬度区间内的样本数量成反比。这种方法产生了一个更均匀和公正的分布，我们可以评估区域，而不是本地，在级联弧成分的变化。使用多元统计方法，我们证明了施密特等人（2008）指定的四个部分实际上在统计上是不同的。然而，使用修改后的层次聚类机制，我们客观地将弧分为六个区域，这些区域的地球化学差异比以前的方案在统计上更显着6.3倍。我们新的、更稳健的分段方案包括加里波第（49.75-51°N）、贝克（48.5-49.75°N）、冰川峰（47.75-48.5°N）、华盛顿（45.75-47.75°N）、地堑（44.25-45.75°N）和南（41.25-44.25°N）分段。通过将弧划分成统计上最不同的部分，并计算每个部分的无偏平均成分，我们探索了原始熔岩成分区域尺度差异的成因。这些自举平均数据表明流体通量签名，地幔肥力，深度和程度的熔融显着的段间差异。我们认为，俯冲几何形状的差异，区域构造和地幔的不均匀性是这些弧内差异的主要原因。
Abstract Primitive and mafic lavas erupted in the Cascades arc of western North America demonstrate significant patterns of along-arc heterogeneity. Such compositional diversity may be the result of differences in mantle melting processes, subduction geometry, regional tectonics, or compositions of the slab, mantle, or overlying lithosphere. Previous authors have partitioned the arc into four geochemically distinct segments in order to assess the importance and relative roles of these processes (Schmidt et al., 2008). However, despite the significant amount of data available from the Cascades arc, no previous study has utilized a statistical approach on a comprehensive dataset to address arc segmentation and its petrogenetic causes. To better characterize the heterogeneity of the entire arc, we first compiled >235,000 isotopic, major, and trace element analyses (glass and whole rock) from over 12,000 samples, which range in composition from mafic to felsic, and include data from arc-front and back-arc centers. We focus on the 2236 mafic arc-front samples in our compilation in order to assess potential causes for along-arc differences in less differentiated magmas, and to potentially lessen any effect of crustal assimilation. To minimize inherent sampling bias – the effect where well-studied volcanoes heavily weight conclusions – we use a weighted bootstrap Monte Carlo approach in which the probability of a sample being selected to the posterior distribution was inversely proportional to the number of samples within its 0.25° latitude bin. This methodology produces a more uniform and unbiased distribution from which we can assess regional, rather than local, compositional variability in the Cascades arc. Using a multivariate statistical approach, we demonstrate that the four segments designated by Schmidt et al. (2008) are, in fact, statistically distinct. However, using a modified hierarchical clustering mechanism, we objectively divide the arc into six regions which have geochemical differences that are up to 6.3 times more statistically significant than in the previous scheme. Our new, more robust segmentation scheme includes the Garibaldi (49.75–51°N), Baker (48.5–49.75°N), Glacier Peak (47.75–48.5°N), Washington (45.75–47.75°N), Graben (44.25–45.75°N), and South (41.25–44.25°N) Segments. By partitioning the arc into the most statistically distinct segments and calculating unbiased mean compositions for each, we explore the petrogenetic causes for the regional-scale differences in primitive lava compositions. These bootstrapped mean data indicate significant inter-segment differences in fluid-flux signature, mantle fertility, and depth and degree of melting. We suggest that differences in subduction geometry, regional tectonics and mantle heterogeneity are the primary causes for these intra-arc differences.