Comparison of Environmental DNA Metabarcoding and Underwater Visual Census for Assessing Macrobenthic Diversity.
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| Format: | Artículo científico |
| Sprache: | en |
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Biology
2025
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| author | Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli |
| author_facet | Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli |
| collection | PubMed - marine biology |
| contents | Comparison of Environmental DNA Metabarcoding and Underwater Visual Census for Assessing Macrobenthic Diversity. Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli The rapid advancement of environmental DNA (eDNA) technology has transformed ecological research, particularly in aquatic ecosystems. However, the optimal sampling matrix (e.g., water or sediment) and the potential for eDNA to replace or complement traditional underwater visual census (UVC) remain unclear. Here, we integrate water eDNA, sediment eDNA, and UVC approaches to systematically compare the diversity of benthic macrofauna in the subtidal zones of the Nanji Islands, China. Our results show that sediment eDNA samples exhibited the highest species richness, while UVC had the lowest. Each method revealed distinct species profiles, with relatively few shared taxa at the order level and below. Environmental eDNA showed significant advantages in detecting key phyla such as Annelida and Arthropoda. In contrast, traditional UVC was crucial for identifying certain taxa, such as Bryozoa, which were undetectable by eDNA methods. The low overlap in species detected by these methods underscores their complementary nature, highlighting the necessity of integrating multiple approaches to achieve a more comprehensive and accurate biodiversity assessment. Future research should focus on refining eDNA techniques, such as developing more universal primers, to further enhance their applicability in biodiversity monitoring. |
| format | Artículo científico |
| id | pubmed_40723380 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Biology |
| record_format | pubmed |
| spellingShingle | Comparison of Environmental DNA Metabarcoding and Underwater Visual Census for Assessing Macrobenthic Diversity. Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli Comparison of Environmental DNA Metabarcoding and Underwater Visual Census for Assessing Macrobenthic Diversity. Zhan, Zifeng Huo, Weiwei Xie, Shangwei Chen, Wandong Liu, Xinming Xu, Kuidong Lei, Yanli The rapid advancement of environmental DNA (eDNA) technology has transformed ecological research, particularly in aquatic ecosystems. However, the optimal sampling matrix (e.g., water or sediment) and the potential for eDNA to replace or complement traditional underwater visual census (UVC) remain unclear. Here, we integrate water eDNA, sediment eDNA, and UVC approaches to systematically compare the diversity of benthic macrofauna in the subtidal zones of the Nanji Islands, China. Our results show that sediment eDNA samples exhibited the highest species richness, while UVC had the lowest. Each method revealed distinct species profiles, with relatively few shared taxa at the order level and below. Environmental eDNA showed significant advantages in detecting key phyla such as Annelida and Arthropoda. In contrast, traditional UVC was crucial for identifying certain taxa, such as Bryozoa, which were undetectable by eDNA methods. The low overlap in species detected by these methods underscores their complementary nature, highlighting the necessity of integrating multiple approaches to achieve a more comprehensive and accurate biodiversity assessment. Future research should focus on refining eDNA techniques, such as developing more universal primers, to further enhance their applicability in biodiversity monitoring. |
| title | Comparison of Environmental DNA Metabarcoding and Underwater Visual Census for Assessing Macrobenthic Diversity. |
| url | https://pubmed.ncbi.nlm.nih.gov/40723380/ |