首页|A novel multi-scale μCT characterization method to quantify biogenic carbonate production

A novel multi-scale μCT characterization method to quantify biogenic carbonate production

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Biogenic carbonate structures such as rhodoliths and foraminiferal-algal nodules are a significant part of marine carbonate production and are being increasingly used as paleoenvironmental indicators for pre-dictive modeling of the global carbon cycle and ocean acidification research.However,traditional meth-ods to characterize and quantify the carbonate production of biogenic nodules are typically limited to two-dimensional analysis using optical and electron microscopy.While micro-computed tomography(μCT)is an excellent tool for 3D analysis of inner structures of geomaterials,the trade-off between sam-ple size and image resolution is often a limiting factor.In this study,we address these challenges by using a novel multi-scale μCT image analysis methodology combined with electron microscopy,to visualize and quantify the carbonate volumes in a biogenic calcareous nodule.We applied our methodology to a foraminiferal-algal nodule collected from the Red Sea along the coast of NEOM,Saudi Arabia.Integrated μCT and SEM image analyses revealed the main biogenic carbonate components of this nodule to be encrusting foraminifera(EF)and crustose coralline algae(CCA).We developed a multi-scale μCT analysis approach for this study,involving a hybrid thresholding and machine-learning based image seg-mentation.We utilized a high resolution μCT scan from the sample as a ground-truth to improve the seg-mentation of the lower resolution full volume μCT scan which provided reliable volumetric quantification of the EF and CCA layers.Together,the EF and CCA layers contribute to approximately 65.5％of the studied FAN volume,corresponding to 69.01 cm3 and 73.32 cm3 respectively,and the rest is comprised of sediment infill,voids and other minor components.Moreover,volumetric quantification results in conjunction with CT density values,indicate that the CCA layers are associated with the highest amount of carbonate production within this foraminiferal-algal nodule.The methodology developed for this study is suitable for analyzing biogenic carbonate structures for a wide array of applications includ-ing quantification of carbonate production and studying the impact of ocean acidification on skeletal structures of marine calcifying organisms.In particular,the hybrid μCT image analysis we adopted in this study proved to be advantageous for the analysis of biogenic structures in which the textures and com-ponents of the internal layers are distinctly visible despite having an overlap in the range of CT density values.

Crustose coralline algaeForaminiferaμCTImage analysisMachine learningMarine carbonate factory

V.Chandra、R.Sicat、F.Benzoni、V.Vahrenkamp、V.Bracchi

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Physical Sciences and Engineering,King Abdullah University of Science and Technology,Thuwal,Saudi Arabia

Saudi Aramco,Dhahran,Saudi Arabia

Visualization Core Lab,King Abdullah University of Science and Technology,Thuwal,Saudi Arabia

Biological and Environmental Science and Engineering,King Abdullah University of Science and Technology,Thuwal,Saudi Arabia

Department of Earth and Environmental Sciences,University of Milano-Bicocca,Milan,Italy

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2024

10.1016/j.gsf.2024.101883

地学前缘(英文版)
中国地质大学（北京） 北京大学

地学前缘(英文版)

CSTPCD
影响因子：0.576
ISSN：1674-9871
年,卷(期)：2024.15(6)