Background: Ferromanganese nodule-bearing deep-sea sediments cover vast areas of the ocean floor, representing a distinctive habitat in the abyss. These sediments harbor unique conditions characterized by high iron concentration and low degradable nutrient levels, which pose challenges to the survival and growth of most microorganisms. While the microbial diversity in ferromanganese nodule-associated sediments has been surveyed several times, little is known about the functional capacities of the communities adapted to these unique habitats. Results: Seven sediment samples collected adjacent to ferromanganese nodules from the Clarion–Clipperton Fracture Zone (CCFZ) in the eastern Pacific Ocean were subjected to metagenomic analysis. As a result, 179 high-quality metagenome-assembled genomes (MAGs) were reconstructed and assigned to 21 bacterial phyla and 1 archaeal phylum, with 88.8% of the MAGs remaining unclassified at the species level. The main mechanisms of resistance to heavy metals for microorganisms in sediments included oxidation (Mn), reduction (Cr and Hg), efflux (Pb), synergy of reduction and efflux (As), and synergy of oxidation and efflux (Cu). Iron, which had the highest content among all metallic elements, may occur mainly as Fe(III) that potentially functioned as an electron acceptor. We found that microorganisms with a diverse array of CAZymes did not exhibit higher community abundance. Instead, microorganisms mainly obtained energy from oxidation of metal (e.g., Mn(II)) and sulfur compounds using oxygen or nitrate as an electron acceptor. Chemolithoautotrophic organisms (Thaumarchaeota and Nitrospirota phyla) were found to be potential manganese oxidizers. The functional profile analysis of the dominant microorganisms further indicated that utilization of inorganic nutrients by redox reactions (rather than organic nutrient metabolism) is a major adaptive strategy used by microorganisms to support their survival in the ferromanganese nodule sediments. Conclusions: This study provides a comprehensive metagenomic analysis of microbes inhabiting metal-rich ferromanganese nodule sediments. Our results reveal extensive redundancy across taxa for pathways of metal resistance and transformation, the highly diverse mechanisms used by microbes to obtain nutrition, and their participation in various element cycles in these unique environments.

The power law particle size distribution (PSD) slope parameter is commonly used to characterize sediment fluxes, resuspension, aggregates, and settling rates in coastal and estuarine waters. However, particle size distribution metrics are also very useful for understanding sediment source and dynamic processes. In this study, a method was proposed to employ the particle size parameters commonly used in sedimentary geology (average particle size (ø), sorting, skewness, and kurtosis) as indicators of changes in sediment dynamic processes, and MODIS images were used to estimate these parameters. The particle size parameters were estimated using a Mie scattering model, Quasi-Analytical Algorithm (QAA) analysis algorithm, and least squares QR decomposition (LSQR) solution method based on the relationship between the power law distribution of the suspended particles and their optical scattering properties. The estimates were verified by field measurements in the Yellow Sea and Bohai Sea regions of China. This method provided good estimates of the average particle size (ø), sorting, and kurtosis. A greater number of wavebands (39) was associated with more accurate particle size distribution curves. Furthermore, the method was used to monitor changes in suspended particulate matter in the vicinity of the Heini Bay of China before and after the passage of a strong storm in August 2011. The particle size parameters represented the influence of a strong typhoon on the distribution of the near-shore sediment and, together with the PSD slope, comprehensively reflected the changes in the near-shore suspended particulate matter. This method not only established the relationship between remote sensing monitoring and the historical sediment record, it also extends the power law model to the application of sediment source and dynamic processes in coastal waters.

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters

It is important to determine the relationship between the concentration of chlorophyll a (Chla) and the inherent optical properties (IOPs) of ocean water to develop optical models and algorithms that characterize the biogeochemical properties and estimate biological pumping and carbon flux in this environment. However, previous studies reported relatively large variations in the particulate backscattering coefficient (b_bp(λ)) and Chla from more eutrophic high-latitude waters to clear oligotrophic waters, especially in oligotrophic oceanic areas where these two variables have little covariation. In this study, we examined the variability of b_bp(λ) and Chla in the euphotic layer in oligotrophic areas of the tropical Western Pacific Ocean and determined the sources of these variations by reassessment of in-situ measurements and the biogeochemical-argo (BGC-Argo) database. Our findings identified covariation of b_bp(λ) and Chla in the water column below the deep Chla maximum (DCM) layer, and indicated that there was no significant correlation relationship between b_bp(λ) and Chla in the upper layer of the DCM. Particles smaller than 3.2 µm that were in the water column above the DCM layer had a large effect on the b_bp(λ) in the vertical profile, but particles larger than 3.2 µm and smaller than 10 µm had the largest effect on the b_bp(λ) in the water column below the DCM layer. The contribution of non-algal particles (NAPs) to backscattering is up to 50%, which occurs in the water depth of 50 m and not consistent with the distribution of Chla. Phytoplankton and NAPs were modeled as coated spheres and homogeneous spherical particles to simulate the b_bp(λ) of the vertical profile by Aden-Kerker method and Mie theory, and the results also indicated that the backscattering caused by particles less than 20 µm were closer to the measured data when they were below and above the DCM layer, respectively. This relationship also reflects the b_bp(λ) of particles in the upper water was significantly affected particle size, but b_bp(λ) in the lower water was significantly affected by Chla concentration. This effect may have relationship with phytoplankton photoacclimation and the relationship of a phytoplankton biomass maximum with particle size distribution in the water column according to the previous relevant studies. These characteristics also had spatial and seasonal variations due to changes of Chla concentration at the surface and at different depths. There was mostly a linear relationship between Chla and b_bp(700) during winter. During other seasons, the relationship between these two variables was better characterized by a power function (or a logarithmic function) in the lower layer of the DCM. The spatial and vertical relationships between the b_bp(λ) and Chla and the corresponding variations in the types of particles described in this study provide parameters that can be used for accurate estimation of regional geochemical processes.