Data Analysis in Deep-Sea Mineral and Organism Interplay: A Review

Authors

  • Yuanqi Pan

DOI:

https://doi.org/10.54097/zt2sav71

Keywords:

Deep-Sea Mineral Resources; Deep-Sea Organisms; Data Analysis Techniques.

Abstract

The deep sea, a realm characterized by extreme environmental conditions and remarkable biodiversity, has become a focal point for both scientific exploration and industrial exploitation. This comprehensive review aims to elucidate the data analysis techniques that are instrumental in studying the complex relationship between deep-sea mineral resources and the organisms that inhabit these extreme environments. The paper begins by outlining the types of deep-sea mineral resources and their distribution, followed by an overview of the methods and technologies used for exploration and extraction. It then delves into the diversity and classification of deep-sea organisms, their unique survival mechanisms, and their ecological roles. The core of the review focuses on data analysis techniques, covering traditional methods, advancements in machine learning and AI, and the inherent challenges and limitations in analyzing intricate deep-sea data. The paper concludes by discussing the direct and indirect impacts of mineral extraction on deep-sea ecosystems, supported by case studies and potential long-term effects on biodiversity and ecosystem health.

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References

Machida, S., & Nakamura, K. Editorial for Special Issue Deep-Sea Ferromanganese Nodules and Related Mineral Resources: Genesis, Exploration, and Mining. Minerals, 2022, 12(6).

Adrien Tran Lu Y, Ruault, S., Daguin-Thiébaut, C., Castel, J., Bierne et al. Subtle limits to connectivity revealed by outlier loci within two divergent metapopulations of the deep-sea hydrothermal gastropod Ifremeria nautilei. Molecular Ecology, 2022.

Lee, G., & Kim, K. Evaluation of Feasibility of Chemical Washing Treatment of Nickel in Deep-sea Mining Tailings by Aluminum Sulfate as Extractant. Korean Society of Environmental Engineers, 2022, 44(3): 77-85.

K. Mizuno, H. Nomaki, Chong Chen, K. Seike. Deep-sea infauna with calcified exoskeletons imaged in situ using a new 3D acoustic coring system (A-core-2000). 2022.

Yangrui Cheng, Yu Dai, Yanyang Zhang, Caihua Yang, Chenglong Liu. Status and Prospects of the Development of Deep-Sea Polymetallic Nodule-Collecting Technology. Sustainability, 2023, 15(5). Petersen, S., Krätschell, A., & Hannington, M. The Current State of Global Activities Related to Deep-sea Mineral Exploration and Mining. EAGE Conference and Exhibition, 2016.

Chen, C., Lin, T.-H., Watanabe, H.K., Akamatsu, T. and Kawagucci, S. Baseline soundscapes of deep-sea habitats reveal heterogeneity among ecosystems and sensitivity to anthropogenic impacts. Limnol Oceanogr. 2021, 66: 3714-3727.

Wang X, Cao Y, Wu S and Yang C. Real-time detection of deep-sea hydrothermal plume based on machine vision and deep learning. Front. Mar. Sci. 2023, 10:1124185. doi: 10.3389/fmars.2023.1124185

Tao Yang, M. Dekkers, Xixi Zhao, K. Petronotis, Y. Chou. Greigite Formation Modulated by Turbidites and Bioturbation in Deep-Sea Sediments Offshore Sumatra. Journal of Geophysical Research: Solid Earth, 2022.

S. Kaiser, Magdalini Christodoulou, A. Janssen, T. Kihara, Inga Mohrbeck, F. Pasotti, S. Schnurr, A. Vink, P. M. Arbizu. Diversity, distribution and composition of abyssal benthic Isopoda in a region proposed for deep-seafloor mining of polymetallic nodules: a synthesis. Marine Biodiversity, 2023.

Syrbu N. S., Hoang Nguyen, Shakirov R. B., Kholmogorov A. O., Venikova A. L., D. A. Le, Legkodimov A. A. Gasgeochemical features in the western part of the East Vietnam Sea (Bien Dong Sea). Vietnam Journal of Marine Science and Technology, 2022.

Yangrui Cheng, Yu Dai, Yanyang Zhang, Caihua Yang, Chenglong Liu. Status and Prospects of the Development of Deep-Sea Polymetallic Nodule-Collecting Technology. Sustainability, 2023.

I. Frutos, S. Kaiser, Łukasz Pułaski, Maciej Studzian, M. Błażewicz. Challenges and Advances in the Taxonomy of Deep-Sea Peracarida: From Traditional to Modern Methods. Frontiers in Marine Science, 2022.

Néstor E Ardila, Gonzalo Giribet, J. A. Sánchez. A time-calibrated molecular phylogeny of the precious corals: reconciling discrepancies in the taxonomic classification and insights into their evolutionary history. BMC Evolutionary Biology, 2012.

[12] L. Lins, D. Zeppilli, L. Menot, et al. Toward a reliable assessment of potential ecological impacts of deep-sea polymetallic nodule mining on abyssal infauna. Limnology and Oceanography: Methods, 2021.

Xiaocheng Wang, Chaolun Li, Minxiao Wang, Ping Zheng. Stable isotope signatures and nutritional sources of some dominant species from the PACManus hydrothermal area and the Desmos caldera. PLOS ONE, 2018.

I. Frutos, S. Kaiser, Łukasz Pułaski, Maciej Studzian, M. Błażewicz. Challenges and Advances in the Taxonomy of Deep-Sea Peracarida: From Traditional to Modern Methods. Frontiers in Marine Science. 2022.

Qianqian Li, Zhenhe Zhai, Qi Li, Lin Wu, L. Bao, Heping Sun. Improved Bathymetry in the South China Sea from Multisource Gravity Field Elements Using Fully Connected Neural Network. Journal of Marine Science and Engineering, 2023.

Li Zhou, Mengna Li, Zhaoshan Zhong, Hao Chen, Minxiao Wang, C. Lian, Hao Wang, Huan Zhang, Lei Cao, Chaolun Li. Toxicological effects of cadmium on deep-sea mussel Gigantidas platifrons revealed by a combined proteomic and metabolomic approach. Frontiers in Marine Science, 2023.

Sahara Ali, Jianwu Wang. MT-IceNet - A Spatial and Multi-Temporal Deep Learning Model for Arctic Sea Ice Forecasting. 2022.

Qiang Wang, Z. Qiu, Shaobo Yang, Hongyu Li, Xingfei Li. Design and experimental research of a novel deep-sea self-sustaining profiling float for observing the northeast off the Luzon Island. 2022.

Gary, S.F., Fox, A.D., Biastoch, A. et al. Larval behaviour, dispersal and population connectivity in the deep sea. Sci Rep. 2020, 10, 10675.

Franke Maximilian, Geier Benedikt, Hammel Jörg U., Dubilier Nicole and Leisch Nikolaus. Coming together—symbiont acquisition and early development in deep-sea bathymodioline musselsProc. R. Soc. 2021, B.2882021104420211044

F. Bonofiglio, F. D. De Leo, Connor Yee, D. Machine learning applied to big data from marine cabled observatories: A case study of sablefish monitoring in the NE Pacific. Chatzievangelou, J. Aguzzi, S. Marini. Frontiers in Marine Science, 2022.

K. Bell, J. S. Chow, Alexis Hope, M. Quinzin, Kathleen Cantner, D. Amon, Jessica E. Cramp, R. Rotjan, Lehua Kamalu, A. de Vos, Sheena Talma, S. Buglass, Veta Wade, Zoleka N Filander, Kaitlin Noyes, Miriam Lynch, A. Knight, N. Lourenço, P. Girguis, J. D. de Sousa, C. Blake, B. Kennedy, T. Noyes, C. McClain. Low-Cost, Deep-Sea Imaging and Analysis Tools for Deep-Sea Exploration: A Collaborative Design Study. Frontiers in Marine Science, 2022.

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Published

13-03-2024