International Journal of Marine Science, 2025, Vol.15, No.1, 28-34 http://www.aquapublisher.com/index.php/ijms 30 3.2 Environmental DNA (eDNA) technology: efficient and non-destructive monitoring The combination of environmental DNA (eDNA) and high-throughput sequencing changes the non-invasive monitoring method of wild fish communities, making fish monitoring more convenient. By analyzing the DNA extracted from water samples, various fish species can be detected without the need for fishing or direct observation (Naz et al., 2023; Ferreira et al., 2024) Environmental DNA technology is applicable to biodiversity surveys in complex sea areas such as Hainan Island and the South China Sea. The use of multi-gene markers (such as COI, 12S rRNA, etc.) can further increase the detection rate and reduce misjudgment (Naz et al., 2023; Ferreira et al., 2024) Integrating eDNA technology into routine monitoring can conduct a more comprehensive assessment of fish resources and provide a scientific basis for conservation policies (Ferreira et al., 2024). 3.3 Genomic and transcriptomic analysis Genomic and transcriptome techniques can precisely identify molecular differences among closely related species. For example, SNP markers can be used to study fish genetic diversity, population structure and adaptability (Figure 1) (Wenne, 2023). These methods can distinguish covert species from hybrid individuals and make up for the deficiencies of traditional techniques (Hubert et al., 2008; Wenne, 2023). Figure 1 An integrated concept map showing the main fields and directions of SNP applications related to aquatic exploited animal populations (Adopted from Wenne, 2023) Because genomic and transcriptome analysis, evolutionary relationships among species, as well as environmental changes or human activities (such as restocking and selective fishing) can have genetic impacts (Wenne, 2023). By analyzing microscopic genetic changes and formulating more scientifically based conservation measures, support is provided for the scientific conservation of fish resources in Hainan Island and the South China Sea (Wenne, 2023; Li, 2024). 4 Application of Intelligent and Integrated Technologies in Fish Identification 4.1 AI image recognition technology Artificial intelligence technology is playing a role in fish monitoring in Hainan Island and the South China Sea. Through deep learning algorithms, computers can automatically identify the types of fish in underwater videos and photos and conduct quantitative statistics (Rauf et al., 2019; Banan et al., 2020; Yang et al., 2020; Malik et al., 2023). This non-contact monitoring method greatly improves work efficiency and is particularly suitable for large-scale ecological surveys. 4.2 Multi-technology fusion recognition Combining multiple recognition methods can obtain more reliable results. For instance, combining spectral analysis techniques with machine learning can distinguish similar fish species more accurately than a single
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