Geology, environment, and life in the deepest part of the world's oceans

Metagenome sequencing and 982 microbial genomes from Kermadec and Diamantina Trenches sediments

Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.

Artificial intelligence for geoscience: Progress, challenges, and perspectives

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

Microbial communities reveal niche partitioning across the slope and bottom zones of the challenger deep

Widespread marine microbiomes exhibit compositional and functional differentiation as a result of adaptation driven by environmental characteristics. We investigated the microbial communities in both seawater and sediments on the slope (7-9 km) and the bottom (9-11 km) of the Challenger Deep of the Mariana Trench to explore community differentiation. Both metagenome-assembled genomes (MAGs) and 16S rRNA amplicon sequence variants (ASVs) showed that the microbial composition in the seawater was similar to that of sediment on the slope, while distinct from that of sediment in the bottom. This scenario suggested a potentially stronger community interaction between seawater and sediment on the slope, which was further confirmed by community assembly and population movement analyses. The metagenomic analysis also indicates a specific stronger potential of nitrate reduction and sulphate assimilation in the bottom seawater, while more versatile nitrogen and sulphur cycling pathways occur on the slope, reflecting functional differentiations among communities in conjunction with environmental features. This work implies that microbial community differentiation occurred in the different hadal niches, and was likely an outcome of microbial adaptation to the extreme hadal trench environment, especially the associated hydrological and geological conditions, which should be considered and measured in situ in future studies.

High hydrostatic pressure stimulates microbial nitrate reduction in hadal trench sediments under oxic conditions

Hadal trenches are extreme environments situated over 6000 m below sea surface, where enormous hydrostatic pressure affects the biochemical cycling of elements. Recent studies have indicated that hadal trenches may represent a previously overlooked source of fixed nitrogen loss; however, the mechanisms and role of hydrostatic pressure in this process are still being debated. To this end, we investigate the effects of hydrostatic pressure (0.1 to 115 MPa) on the chemical profile, microbial community structure and functions of surface sediments from the Mariana Trench using a Deep Ocean Experimental Simulator supplied with nitrate and oxygen. We observe enhanced denitrification activity at high hydrostatic pressure under oxic conditions, while the anaerobic ammonium oxidation - a previously recognized dominant nitrogen loss pathway - is not detected. Additionally, we further confirm the simultaneous occurrence of nitrate reduction and aerobic respiration using a metatranscriptomic dataset from in situ RNA-fixed sediments in the Mariana Trench. Taken together, our findings demonstrate that hydrostatic pressure can influence microbial contributions to nitrogen cycling and that the hadal trenches are a potential nitrogen loss hotspot. Knowledge of the influence of hydrostatic pressure on anaerobic processes in oxygenated surface sediments can greatly broaden our understanding of element cycling in hadal trenches.

Hidden dangers: High levels of organic pollutants in hadal trenches

The "V"-shaped structure of hadal trenches acts as a natural collector of organic pollutants, drawing attention to the need for extensive research in these areas. Our review identifies significant concentrations of organic pollutants, including persistent organic pollutants, black carbon, antibiotic-resistant genes, and plastics, which often match those in industrialized regions. They may trace back to both human activities and natural sources, underscoring the trenches' critical role in ocean biogeochemical cycles. We highlight the complex lateral and vertical transport mechanisms within these zones. Advanced methodologies, including stable isotope analysis, biomarker identification, and chiral analysis within isotope-based mixing models, are crucial for discerning the origins and pathways of these pollutants. In forthcoming studies, we aim to explore advanced methods for precise pollutant tracing, develop predictive models to forecast the future distribution and impacts of pollutants in hadal zones and on the Earth's larger ecological systems.

Analysis of Stray Light and Enhancement of SNR in DMD-Based Spectrometers

Due to advantages such as the high efficiency of light utilization, small volume, and vibration resistance, digital micro-mirror device (DMD)-based spectrometers are widely used in ocean investigations, mountain surveys, and other field science research. In order to eliminate the stray light caused by DMDs, the stray light in DMD-based spectrometers was first measured and analyzed. Then, the stray light was classified into wavelength-related components and wavelength-unrelated components. Moreover, the noise caused by the stray light was analyzed from the perspective of encoding equation, and the de-noising decoding equation was deduced. The results showed that the accuracy range of absorbance was enhanced from [0, 1.9] to [0, 3.1] in single-stripe mode and the accuracy range of absorbance was enhanced from [0, 3.8] to [0, 6.3] in Hadamard transform (HT) multiple-stripe mode. A conclusion can be drawn that the de-noising strategy is feasible and effective for enhancing the SNR in DMD-based spectrometers.

A Prototype Design and Sea Trials of an 11,000 m Autonomous and Remotely-Operated Vehicle Dream Chaser

To better study the biology and ecology of hadal trenches for marine scientists, the Hadal Science and Technology Research Center (HAST) of Shanghai Ocean University proposed to construct a movable laboratory that includes a mothership, several full-ocean-depth (FOD) submersibles, and FOD landers to obtain samples in the hadal trenches. Among these vehicles, the project of an FOD autonomous and remotely-operated vehicle (ARV) named “Dream Chaser” was started in July 2018. The ARV could work in both remotely-operated and autonomous-operated modes, and serves large-range underwater observation, on-site sampling, surveying, mapping, etc. This paper proposed a novel three-body design of the FOD ARV. A detailed illustration of the whole system design method is provided. Numerical simulations and experimental tests for various sub-systems and disciplines have been conducted, such as resistance analysis using the computational fluid mechanics method and structural strength analysis for FOD hydrostatic pressure using the finite element method and pressure chamber tests. In addition, components tests and the entire system tests have been performed on land, underwater, and in the pressure chamber in the laboratory of HAST, and the results are discussed. Extensive experiments of two critical components, i.e., the thrusters and ballast-abandoning system, have been conducted and further analyzed in this paper. Finally, the procedures and results of lake trials, South China Sea trials and the first phase of Mariana Trench sea trials of the ARV in 2020 are also introduced. This paper provides a design method for the novel three-body FOD ARV. More importantly, the lessons learned from the FOD pressure test, lake tests, and sea trials, no matter the success or failure, will guide future endeavors and the application of ARV Dream Chaser and underwater vehicles of this kind.

Analysis, Simulation and Experimental Study of the Tensile Stress Calibration of Ceramic Cylindrical Pressure Housings

Engineering ceramics have extremely high values for both specific modulus and specific compressive strength, making them one of the most promising materials for enhancing the carrying capability of full ocean depth (FOD) submersibles. However, due to the low tensile strength of most ceramic materials, the tensile stress generated at the contact surface of ceramic pressure housings under hydrostatic pressure may exceed the material’s limits and thus lead to cracking failure. Currently, there are no valid calibration methods for the tensile stress caused by material discontinuities at the contact surface. In this paper, an approximate model is established based on contact mechanics. The absolute error of the approximate model, as verified by the simulation results for nine groups of ceramic pressure housings, does not exceed 14.2%. It is also concluded that the smaller the difference in Young’s modulus between the ceramics and metals, the higher the tensile strength safety factor. In addition, two hydrostatic pressure experiments were carried out to further verify the results of the approximate model and the numerical solutions. The approximate model is oriented to the reliable design of ceramic pressure housings. It will play an important role in improving the carrying capacity and observation capability of FOD submersibles.

Dawn of complex animal food webs: A new predatory anthozoan (Cnidaria) from Cambrian

Cnidarians diverged very early in animal evolution; therefore, investigations of the morphology and trophic levels of early fossil cnidarians may provide critical insights into the evolution of metazoans and the origin of modern marine food webs. However, there has been a lack of unambiguous anthozoan cnidarians from Ediacaran assemblages, and undoubted anthozoans from the Cambrian radiation of metazoans are very rare and lacking in ecological evidence. Here, we report a new polypoid cnidarian, Nailiana elegans gen. et sp. nov., represented by multiple solitary specimens from the early Cambrian Chengjiang biota (∼520 Ma) of South China. These specimens show eight unbranched tentacles surrounding a single opening into the gastric cavity, which may have born multiple mesenteries. Thus, N. elegans displays a level of organization similar to that of extant cnidarians. Phylogenetic analyses place N. elegans in the stem lineage of Anthozoa and suggest that the ancestral anthozoan was a soft-bodied, solitary polyp showing octoradial symmetry. Moreover, one specimen of the new polyp preserves evidence of predation on an epifaunal lingulid brachiopod. This case provides the oldest direct evidence of macrophagous predation, the advent of which may have triggered the emergence of complex trophic/ecological relationships in Cambrian marine communities and spurred the explosive radiation of animal body plans.

•

Polypoid animal from early Cambrian of China is a stem-group anthozoan cnidarian

•

Anthozoan ancestor inferred to be soft-bodied, solitary polyp of octoradial symmetry

•

The new anthozoan provides the oldest direct evidence of macrophagous predation

•

Macrophagous predation may have triggered complex food webs in early Cambrian

The Color Improvement of Underwater Images Based on Light Source and Detector

As one of the most direct approaches to perceive the world, optical images can provide plenty of useful information for underwater applications. However, underwater images often present color deviation due to the light attenuation in the water, which reduces the efficiency and accuracy in underwater applications. To improve the color reproduction of underwater images, we proposed a method with adjusting the spectral component of the light source and the spectral response of the detector. Then, we built the experimental setup to study the color deviation of underwater images with different lamps and different cameras. The experimental results showed that, a) in terms of light source, the color deviation of an underwater image with warm light LED (Light Emitting Diode) (with the value of Δa*2+Δb*2 being 26.58) was the smallest compared with other lamps, b) in terms of detectors, the color deviation of images with the 3×CMOS RGB camera (a novel underwater camera with three CMOS sensors developed for suppressing the color deviation in our team) (with the value of Δa*2+Δb*2 being 25.25) was the smallest compared with other cameras. The experimental result (i.e., the result of color improvement between different lamps or between different cameras) verified our assumption that the underwater image color could be improved by adjusting the spectral component of the light source and the spectral response of the detector. Differing from the color improvement method with image processing, this color-improvement method was based on hardware, which had advantages, including more image information being retained and less-time being consumed.

Role of deep-sea equipment in promoting the forefront of studies on life in extreme environments

The deep-sea environment creates the largest ecosystem in the world with the largest biological community and extensive undiscovered biodiversity. Nevertheless, these ecosystems are far from well known. Deep-sea equipment is an indispensable approach to research life in extreme environments in the deep-sea environment because of the difficulty in obtaining access to these unique habitats. This work reviewed the historical development and the state-of-the-art of deep-sea equipment suitable for researching extreme ecosystems, to clarify the role of this equipment as a promoter for the progress of life in extreme environmental studies. Linkages of the developed deep-sea equipment and the discovered species are analyzed in this study. In addition, Equipment associated with researching the deep-sea ecosystems of hydrothermal vents, cold seeps, whale falls, seamounts, and oceanic trenches are introduced and analyzed in detail. To clarify the thrust and key points of the future promotion of life in extreme environmental studies, prospects and challenges related to observing equipment, samplers, laboratory simulation systems, and submersibles are proposed. Furthermore, a blueprint for the integration of in situ observations, sampling, controllable culture, manned experiments in underwater environments, and laboratory simulations is depicted for future studies.

Untangling Microbiota Diversity and Assembly Patterns in the World's Largest Water Diversion Canal

Large water diversion projects are important constructions for reallocation of human-essential water resources. Deciphering microbiota dynamics and assembly mechanisms underlying canal water ecosystem services especially during long-distance diversion is a prerequisite for water quality monitoring, biohazard warning and sustainable management. Using a 1432-km canal of the South-to-North Water Diversion Projects as a model system, we answer three central questions: how bacterial and micro-eukaryotic communities spatio-temporally develop, how much ecological stochasticity contributes to microbiota assembly, and which immigrating populations better survive and navigate across the canal. We applied quantitative ribosomal RNA gene sequence analyses to investigate canal water microbial communities sampled over a year, as well as null model- and neutral model-based approaches to disentangle the microbiota assembly processes. Our results showed clear microbiota dynamics in community composition driven by seasonality more than geographic location, and seasonally dependent influence of environmental parameters. Overall, bacterial community was largely shaped by deterministic processes, whereas stochasticity dominated micro-eukaryotic community assembly. We defined a local growth factor (LGF) and demonstrated its innovative use to quantitatively infer microbial proliferation, unraveling taxonomically dependent population response to local environmental selection across canal sections. Using LGF as a quantitative indicator of immigrating capacities, we also found that most micro-eukaryotic populations (82%) from the source water sustained growth in the canal and better acclimated to the hydrodynamical water environment than bacteria (67%). Taxa inferred to largely propagate include Limnohabitans sp. and Cryptophyceae, potentially contributing to water auto-purification. Combined, our work poses first and unique insights into the microbiota assembly patterns and dynamics in the world's largest water diversion canal, providing important ecological knowledge for long-term sustainable water quality maintenance in such a giant engineered system.