Collaborative Research: Towards quantifying eruptive timing and volcanic accretion on the Southern East Pacific Rise

合作研究：东太平洋南部隆起的喷发时间和火山吸积地球表面70%的面积被海底洋脊火山形成的洋壳所覆盖。准确地描述海底熔岩流的大小、形状和频率对于了解大洋中脊火山系统是如何工作的很重要。美国国家科学院最近的一份报告指出，对火山喷发规模和频率的描述是火山科学中突出的重大挑战之一。然而，由于测年技术不充分，以及与从海底进行观测和采集样本有关的相当大的技术挑战，区分和准确测定个别海底熔岩流的时间仍然具有挑战性。该项目采用多种方法来测量南东太平洋隆起(南太平洋的一个洋脊)的喷发时间。来自自动驾驶水下机器人(AUV-自主水下机器人)的数据将与潜水观测和样本采集相结合。样品化学和磁信号有助于确定地表流动的年龄和喷发频率，而AUV数据提供了高分辨率的海底地图和与地下熔岩流分布有关的其他信息。结果将被合并到一个模型中，该模型可以用于其他大洋中脊设置。拟议的工作将提供与东太平洋隆起北部9°N部分的比较，扩大少数深入研究的脊段。海底熔岩流的大小、形状和喷发频率是我们理解许多大洋中脊过程的重要一阶变量，包括火山构造；岩浆补给、通量和储存；以及热液系统和生物群落的稳定性。美国国家科学院最近的一份报告指出，火山喷发大小和频率的量化是火山科学中突出的重大挑战之一不可或缺的一部分。然而，由于辐射测量技术不足，以及在海底进行观测和采集样本方面存在相当大的技术挑战，区分地质记录中的个别海底水流并准确测定其年代仍然具有挑战性。此外，对于一个间歇性的过程，没有一个普遍接受的统计框架来报告或解释爆发间隔。虽然在EPR上和胡安德富卡山脊的轴向海山上记录北纬9°处的喷发历史已经做出了相当大的努力，但限制一个时空可变的全球系统需要更多的数据，也许还需要新的方法。拟议的工作采用了一种综合方法，通过将自动水下航行器(AUV)测绘与HOV(载人潜航器)观测和样本收集结合起来，量化东太平洋南部隆起的喷发时间。接近底部的侧扫和测深数据将指导采样位置，并提供重要的解释背景，以及计算流量的可能性。地球化学数据将与地磁古强度提供的时间约束相结合，以确定喷发团。近底部磁异常数据将被用来将地表古地磁数据与深度积分信号联系起来，并对流动分布的三维统计模型提供重要约束，该模型也受到根据现有地震反射数据估计的2A层厚度的约束。结合起来，这些方法将能够识别流动单元，量化喷发频率，并评估沉积过程。所得到的统计模型可以对照其他大洋中脊环境进行测试和应用。此外，拟议的工作将提供与研究充分的9°N段的对比，并扩展少量深入研究的脊段。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Collaborative Research: Eruptive timing and volcanic accretion on the Southern East Pacific RiseSeventy percent of Earth’s surface is covered by ocean crust created by volcanoes at underwater mid-ocean ridges. It is important to accurately describe the size, shape, and frequency of submarine lava flows to understand how mid-ocean ridge volcanic systems work. A recent National Academies report identifies description of eruptive sizes and frequencies as one of the outstanding grand challenges in volcano science. However, distinguishing and accurately dating individual submarine lava flows remains challenging due to inadequate dating techniques, as well as considerable technical challenges associated with making observations and collecting samples from the seafloor. This project takes multiple approaches to measuring eruptive timing on the Southern East Pacific Rise (a mid-ocean ridge in the south Pacific). Data from self-driving underwater vehicles (AUV-autonomous underwater vehicle) will be combined with submersible observations and sample collection. Sample chemistry and magnetic signals help determine age and eruption frequency of surface flows, while the AUV data provide high-resolution mapping of the sea floor and additional information related to sub-surface lava flow distributions. The results will be combined into a model that can be and applied to other mid-ocean ridge settings. The proposed work will provide a comparison to the well-studied 9°N section of the northern East Pacific Rise, expanding the small number of intensively-studied ridge segments.The size, shape, and eruptive frequency of submarine lava flows are important first-order variables in our understanding of many mid-ocean ridge processes, including volcanic construction; magma recharge, flux, and storage; and the stability of hydrothermal systems and biological communities. A recent National Academies report identifies the quantification of eruptive sizes and frequencies as integral to one of the outstanding grand challenges in volcano science. However, distinguishing and accurately dating individual submarine flows in the geological record remains challenging due to inadequate radiometric techniques, as well as the considerable technical challenges associated with making observations and collecting samples from the seafloor. Further, for a process that is episodic, there is no commonly-accepted statistical framework for reporting or interpreting eruptive intervals. While considerable effort has gone into documenting eruptive history at 9°N on EPR and at Axial seamount on the Juan de Fuca Ridge, constraining a spatially and temporally variable global system requires significantly more data, and perhaps new approaches. The proposed work takes an integrated approach to quantifying eruptive timing on the Southern East Pacific Rise by combining AUV (autonomous underwater vehicle) mapping with HOV (human occupied vehicle) observations and sample collection. Near-bottom sidescan and bathymetric data will guide sampling locations and provide important interpretive context, as well as the possibility of calculating flow volumes. Geochemical data will be combined with temporal constraints provided by geomagnetic paleointensity to define eruptive clusters. Near-bottom magnetic anomaly data will be used to link the surface paleomagnetic data with a depth-integrated signal and provide important constraints on 3D statistical models of flow distributions, which are also constrained by estimates of layer 2A thickness from existing seismic reflection data. Combined, these methods will enable identification of flow units, quantifying eruptive frequency, and assessing accretionary processes. The resulting statistical model can be tested against and applied to other mid-ocean ridge settings. Further, the proposed work will provide a point of contrast to the well-studied 9°N segment and expand the small number of intensively-studied ridge segments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.