16:00 〜 16:15
[SCG48-15] 独立成分分析に基づく沖縄トラフ海底熱水鉱床の多元素組成の特徴
キーワード：熱水性鉱床、沖縄トラフ、海底鉱物資源、多変量解析、独立成分分析
Submarine hydrothermal activity constitutes a key process that transfers energy and materials from the Earth’s interior to surficial systems including hydrosphere and biosphere. Producing mineral deposits of economic interest is also an important aspect of such a physicochemical process. In the Okinawa Trough, a back-arc basin bearing multiple hydrothermal deposits [1], a number of scientific research cruises have been conducted [1-5]. Previous studies have implemented a variety of geochemical and mineralogical analyses and discussed the ore-forming processes [4,5], using drilling core samples containing various altered/unaltered volcaniclastic and hemipelagic sediments, as well as sulfidic rocks, obtained by the drilling vessel CHIKYU.
In this study, we statistically analyzed a comprehensive dataset of bulk chemical composition (>1,300 samples x 47 element contents) of the drilling core samples using independent component analysis (ICA). ICA is a powerful method to recover mutually independent signals from an observed mixture of the source signals, which has been successfully applied to geochemical datasets [6-8]. In the presentation, we will discuss the features and spatial distributions of the statistically independent components that reflect multi-elemental information and characterize the (sub)seafloor hydrothermal deposits in the study area.
[1] Glasby and Notsu (2003) Ore. Geol. Rev. 23, 299-339. [2] Nakajima et al. (2015) PLoS One. 10, e0123095. [3] Nozaki et al. (2016) Sci. Rep. 6, 22163. [4] Totsuka et al. (2019) Chem. Geol. 514, 90-104. [5] Nozaki et al. (2021) Sci. Rep. 11, 8809. [6] Iwamori & Albarède (2008) Geochem. Geophys. Geosyst. 9, Q04033. [7] Yasukawa et al. (2016) Sci. Rep. 6, 29603. [8] Yasukawa et al. (2019) Geochem. Geophys. Geosyst. 20, 3402-3430.
In this study, we statistically analyzed a comprehensive dataset of bulk chemical composition (>1,300 samples x 47 element contents) of the drilling core samples using independent component analysis (ICA). ICA is a powerful method to recover mutually independent signals from an observed mixture of the source signals, which has been successfully applied to geochemical datasets [6-8]. In the presentation, we will discuss the features and spatial distributions of the statistically independent components that reflect multi-elemental information and characterize the (sub)seafloor hydrothermal deposits in the study area.
[1] Glasby and Notsu (2003) Ore. Geol. Rev. 23, 299-339. [2] Nakajima et al. (2015) PLoS One. 10, e0123095. [3] Nozaki et al. (2016) Sci. Rep. 6, 22163. [4] Totsuka et al. (2019) Chem. Geol. 514, 90-104. [5] Nozaki et al. (2021) Sci. Rep. 11, 8809. [6] Iwamori & Albarède (2008) Geochem. Geophys. Geosyst. 9, Q04033. [7] Yasukawa et al. (2016) Sci. Rep. 6, 29603. [8] Yasukawa et al. (2019) Geochem. Geophys. Geosyst. 20, 3402-3430.