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GIS-Based Remote Sensing Image Information Analysis of the South Atlantic Ecological Environment and Diversity of Deep-Sea Microorganism with Antifungal Effects

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  • Jingjing Xu
  • Peisheng Yan
  • Miaochao Chen

Abstract

This paper uses the GIS technology to collect location and geographic information of the South Atlantic ecological environment and then uses the remote sensing image technology to extract and analyse the collected information to provide a strong basis for maintaining a healthy marine ecological environment. Based on multitemporal remote sensing images, this paper constructs an ecological vulnerability evaluation model for marine by coupling several ecological indicators, analyses the status of marine ecological environment and its dynamic changes, explores the driving factors of its changes, further analyses the relationship between ecological vulnerability, land use changes, and landscape patterns, and proposes targeted ecological protection countermeasures for marine ecological environment. This paper analyses and studies the quality control mechanism of marine environment monitoring data, the construction of marine environment evaluation model, and the automation of evaluation and early warning response based on the application of GIS, with the support of marine environment evaluation and early warning business, to enhance the availability and integrity of marine environment monitoring data, improve the execution efficiency of marine environment evaluation business and early warning response, reduce the risk of marine environment emergencies, and realize the integration and intelligence of marine environment evaluation and early warning, to improve the level of Informa ionization and management of marine environment evaluation business in marine management departments. The operational watershed ecological environment monitoring service system built in this paper, which integrates GIS, RS, GPS, data warehouse, and other information technologies, has the advantages of high accuracy of information extraction, convenient data management, good portability, and strong operability, which can provide a scientific basis for the unified scheduling management of the marine environment, ecological environment evaluation, and sustainable development planning of the economy, and it is of great theoretical and practical significance and can be used in other watersheds. Meanwhile, the unique environment of the ocean has endowed the marine microorganism with affluent diversity, which can display a variety of bioactivities. In this study, thirty-two seawater and sediment samples were collected from different depths within the scope of 5 m to 3203 m at 18 sampling sites in the South Atlantic Ocean. 1017 culturable strains were obtained after isolation and identification. The tip culture method was used to screen strains with antifungal and antiaflatoxigenic activities. The tip culture results showed that a total of thirty-one marine strains were confirmed to have significant antagonism against aflatoxin production with an inhibition ratio exceeding 80%, including 11 strains with a mycelial growth inhibition ratio exceeding 80% simultaneously. The variability of culturable bacterial distribution and diversity were studied by phylogenetic analysis of 16S rRNA sequences. Phylogenetic analysis of 16S rRNA sequences revealed a significant diversity of culturable strains. A total of 31 strains clustered into 13 genera: Marinobacter sp., Pseudomonas sp., Alteromonas sp., Idiomarina sp., Halomonas sp., Alcanivorax sp., Thalassospira sp., Jannaschia sp., Stakelama sp., Erythrobacter sp., Chengkuizengella sp., Bacillus sp., and Microbacterium sp. The 31 strains with antifungal and antiaflatoxigenic activities were dominated by populations of strains belonging to the genus Thalassospira (19.35%). To the best of our knowledge, this is also the first report to analyse the diversity of culturable bacteria with antifungal and antiaflatoxigenic activities in the South Atlantic Ocean from three perspectives: different media, different sampling stations, and different sampling depths.

Suggested Citation

  • Jingjing Xu & Peisheng Yan & Miaochao Chen, 2022. "GIS-Based Remote Sensing Image Information Analysis of the South Atlantic Ecological Environment and Diversity of Deep-Sea Microorganism with Antifungal Effects," Advances in Mathematical Physics, Hindawi, vol. 2022, pages 1-16, January.
  • Handle: RePEc:hin:jnlamp:1677858
    DOI: 10.1155/2022/1677858
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