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  1. Abstract

    The past ∼200 million years of Earth's geomagnetic field behavior have been recorded within oceanic basalts, many of which are only accessible via scientific ocean drilling. Obtaining the best possible paleomagnetic measurements from such valuable samples requires an a priori understanding of their magnetic mineralogies when choosing the most appropriate protocol for stepwise demagnetization experiments (either alternating field or thermal). Here, we present a quick, and non‐destructive method that utilizes the amplitude‐dependence of magnetic susceptibility to screen submarine basalts prior to choosing a demagnetization protocol, whenever conducting a pilot study or other detailed rock‐magnetic characterization is not possible. We demonstrate this method using samples acquired during International Ocean Discovery Program Expedition 391. Our approach is rooted in the observation that amplitude‐dependent magnetic susceptibility is observed in basalt samples whose dominant magnetic carrier is multidomain titanomagnetite (∼TM60–65, (Ti0.60–0.65Fe0.35–0.40)Fe2O4). Samples with low Ti contents within titanomagnetite or samples that have experienced a high degree of oxidative weathering do not display appreciable amplitude dependence. Due to their low Curie temperatures, basalts that possess amplitude‐dependence should ideally be demagnetized either using alternating fields or via finely‐spaced thermal demagnetization heating steps below 300°C. Our screening method can enhance the success rate of paleomagnetic studies of oceanic basalt samples.

     
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    Free, publicly-accessible full text available February 1, 2025
  2. Abstract

    Valdivia Bank (VB) is a Late Cretaceous oceanic plateau formed by volcanism from the Tristan‐Gough hotspot at the Mid‐Atlantic Ridge (MAR). To better understand its origin and evolution, magnetic data were used to generate a magnetic anomaly grid, which was inverted to determine crustal magnetization. The magnetization model reveals quasi‐linear polarity zones crossing the plateau and following expected MAR paleo‐locations, implying formation by seafloor spreading over ∼4 Myr during the formation of anomalies C34n‐C33r. Paleomagnetism and biostratigraphy data from International Ocean Discovery Program Expedition 391 confirm the magnetic interpretation. Anomaly C33r is split into two negative bands, likely by a westward ridge jump. One of these negative anomalies coincides with deep rift valleys, indicating their age and mechanism of formation. These findings imply that VB originated by seafloor spreading‐type volcanism during a plate reorganization, not from a vertical stack of lava flows as expected for a large volcano.

     
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  3. Abstract

    We demonstrate the efficacy of a Bayesian statistical inversion framework for reconstructing the likely characteristics of large pre‐instrumentation earthquakes from historical records of tsunami observations. Our framework is designed and implemented for the estimation of the location and magnitude of seismic events from anecdotal accounts of tsunamis including shoreline wave arrival times, heights, and inundation lengths over a variety of spatially separated observation locations. The primary advantage of this approach is that all of the assumptions made in the inversion process are incorporated explicitly into the mathematical framework. As an initial test case we use our framework to reconstruct the great 1852 earthquake and tsunami of eastern Indonesia. Relying on the assumption that these observations were produced by a subducting thrust event, the posterior distribution indicates that the observables were the result of a massive mega‐thrust event with magnitude near 8.8 Mw and a likely rupture zone in the north‐eastern Banda arc. The distribution of predicted epicentral locations overlaps with the largest major seismic gap in the region as indicated by instrumentally recorded seismic events. These results provide a geologic and seismic context for hazard risk assessment in coastal communities experiencing growing population and urbanization in Indonesia. In addition, the methodology demonstrated here highlights the potential for applying a Bayesian approach to enhance understanding of the seismic history of other subduction zones around the world.

     
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