Diversity of eukaryotic micro-organisms and changes in the dominant fungal taxa composition in relationship with soil environment in the Ebinur Lake wetland

Composition and diversity of the fungal community in the rhizosphere soil of halophytic vegetation in Ebinur Lake wetland

The Ebinur Lake wetland in Xinjiang is a typical wetland, comprising a desert ecosystem with rich soil microbial resources, especially soil fungi in the inter-rhizosphere regions of the wetland plants. This study aimed to clarify the diversity and community structures of the inter-rhizosphere soil fungi of plants in areas of high salinity in the Ebinur Lake wetland and their correlations with environmental factors, as little is currently known on this topic. The diversity and differences in the community structures of fungi associated with 12 salt-tolerant plant species in the Ebinur Lake wetland were investigated using 16S rRNA sequencing. Correlations between the fungi and environmental factors, specifically, the physiochemical characteristics of the soil, were evaluated. The results showed that fungal diversity was highest in the rhizosphere soil of Haloxylon ammodendron, followed by H. strobilaceum. The dominant fungal groups were found to be Ascomycota and Basidiomycota, and the dominant genus was Fusarium. Redundancy analysis revealed significant associations between total nitrogen, electrical conductivity, and total potassium in the soil and both the diversity and abundance of the fungi (P < 0.05). Furthermore, the abundance of fungi of all genera in the rhizosphere soil samples were found to be strongly correlated with environmental physicochemical factors such as available nitrogen and phosphorus. These findings provide data and theoretical support for a better understanding of the ecological resources of fungi in the Ebinur Lake wetland.

Distribution patterns and community assembly processes of eukaryotic microorganisms along an altitudinal gradient in the middle reaches of the Yarlung Zangbo River

Eukaryotic microorganisms play an important role in the biogeochemical cycles of rivers. Dynamic hydrological processes in rivers are thought to influence the assembly processes of eukaryotic microbes, as well as affecting local geomorphology. These processes have not been extensively studied for eukaryotic river microbes in extreme environments on the Tibetan Plateau. This study used 18S rDNA gene amplification sequencing, a neutral community model, and a null model to analyze the spatial and temporal dynamics and assembly processes of eukaryotic microbial communities in the middle reaches of the Yarlung Zangbo River. We conducted analyses across wet and dry seasons, as well as varying altitudinal gradients. Our results showed that the diversity, structure, and taxonomic composition of eukaryotic microbial communities varied more with altitude than season, and the diversity of the communities first increased, then decreased, with increasing elevation. Distance-decay analysis showed that the correlation between eukaryotic microbial communities and environmental distance was stronger than the correlation between the microbial communities and geographical distance. Deterministic processes (homogeneous selection) dominated the construction of eukaryotic microbial communities, and water temperature, pH, and total phosphorus were the primary environmental factors that influenced the construction of eukaryotic microbial communities. These results expand our understanding of the characteristics of eukaryotic microbial communities in rivers on the Tibetan Plateau and provide clues to understanding the mechanisms that maintain eukaryotic microbial diversity in extreme environments.

Satellite taxa regulated the response of constructed wetlands microeukaryotic community to changing hydraulic loading rate

Revealing how species interaction and assembly processes structure the core and satellite microeukaryotic subcommunities in an engineering environment is crucial for understanding how biodiversity influences system function. By investigating the core and satellite microeukaryotic subcommunities in constructed wetlands (CWs), we depicted an integrated distribution pattern of microeukaryotic communities in the CWs with different hydraulic loading rates (HLRs). Surprisingly, our results suggested that high HLR reduced the diversity and network stability of the microeukaryote community in CW. The stochastic process becomes more important with the increased HLR. In addition, satellite and core taxa varied inconsistently under different HLRs except for niche breadth. And the changes in all taxa were consistent with those in satellite taxa. Satellite taxa, but not core taxa, was an important driver in shaping the dynamics of microeukaryotic communities and played an important role in maintaining the stability of the microeukaryotic community. Overall, our results not only fill a gap in understanding the microeukaryotic community dynamics and its basic drivers of CWs under different HLRs but also highlights the particular importance of satellite microeukaryotes in mediating biogeochemical cycles in CWs ecosystems.

Regional suitability prediction of soil salinization based on remote-sensing derivatives and optimal spectral index

Soil salinization is an extremely serious land degradation problem in arid and semi-arid regions that hinders the sustainable development of agriculture and food security. Information and research on soil salinity using remote sensing (RS) technology provide a quick and accurate assessment and solutions to address this problem. This study aims to compare the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction and exploration of the potential application of derivatives to RS prediction of salinized soils. It explores the ability of derivatives to be used in the Landsat-8 OLI and Sentinel-2A MSI multispectral data, and it was used as a data source as well as to address the adaptability of salinity prediction on a regional scale. The two-dimensional (2D) and three-dimensional (3D) optimal spectral indices are used to screen the bands that are most sensitive to soil salinity (0-10 cm), and RS data and topographic factors are combined with machine learning to construct a comprehensive soil salinity estimation model based on gray correlation analysis. The results are as follows: (1) The optimal spectral index (2D, 3D) can effectively consider possible combinations of the bands between the interaction effects and responding to sensitive bands of soil properties to circumvent the problem of applicability of spectral indices in different regions; (2) Both the Landsat-8 OLI and Sentinel-2A MSI multispectral RS data sources, after the first-order derivative techniques are all processed, show improvements in the prediction accuracy of the model; (3) The best performance/accuracy of the predictive model is for sentinel data under first-order derivatives. This study compared the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction in finding the potential application of derivatives to RS prediction of salinized soils, with the results providing some theoretical basis and technical guidance for salinized soil prediction and environmental management planning.

Catabolic Activity and Structural Diversity of Bacterial Community in Soil Covered by Halophytic Vegetation

The catabolic activity and structural diversity of soil bacteria covered by five different halophytic vegetation types in the Yellow River Delta affected by long-term salinization were studied using Biolog-Eco technology. The result showed that soil quality, the diversity, and catabolic activity of the bacterial community of mildly salt-tolerant vegetation (Imperata cylindrical (L.) Beauv. and Apocynum venetum L.) were significantly higher than those of the bacterial community of highly salt-tolerant vegetation (Suaeda salsa (L.) Pall., Aeluropus sinensis (D.) Tzvel.), while these values were lowest for bacterial communities in bare land. The operational taxonomic units (OTUs) and diversity indexes of soil bacteria covered by Aeluropus sinensis were higher than those of soil bacteria covered by other types of vegetation, while those of soil bacteria covered by bare land were lowest. Principal component analysis (PCA) of the carbon source utilization capacity of the soil bacterial communities showed that organic acids, polymers, and amino acids were sensitive carbon sources that enabled study of the diversity of carbon metabolic functions in soil bacterial communities. And redundancy analysis (RDA) showed that D-galacturonic was significantly positively correlated with Verrucomicrobia, which further demonstrated the effect of organic acid carbon sources on metabolic functional diversity of soil bacterial communities in the Yellow River Delta.