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Get Free AccessMesopelagic fish are among the most abundant vertebrates on Earth and play a crucial role in carbon sequestration through their daily vertical migration. However, their dietary ecology remains poorly understood, especially in the Red Sea, limiting our grasp of their trophic interactions and ecological roles. This study investigates the dietary composition of two common mesopelagic fish species in the Red Sea, the lanternfish (Benthosema taxa) and the endemic lightfish (Vinciguerria mabahiss), using DNA metabarcoding of the mitochondrial COI marker, supplemented by remotely operated vehicle (ROV) video observations. Our findings show that V. mabahiss exhibits higher prey diversity compared to Benthosema taxa, suggesting a more generalist feeding strategy. Both species primarily consume copepods, likely due to the high abundance of copepods in the upper 200 m of the Red Sea. Despite this commonality, distinct dietary niches were observed: Benthosema taxa consumes significant amounts of molluscs, followed by annelids and echinoderms, while V. mabahiss occasionally consumes gelatinous prey such as hydrozoans and scyphozoans. Notably, our ROV video footage demonstrates that these mesopelagic fish engage in benthic feeding on the continental slope, a behavior rarely documented. By consuming and redistributing organic material through their diel vertical migrations, mesopelagic fish contribute to the biological carbon pump, with important implications for carbon sequestration processes in the ocean. Future studies integrating DNA metabarcoding with stable isotope analysis could provide deeper insights into dietary partitioning and the ecological contributions of these mesopelagic fish species to the Red Sea ecosystem and beyond.
Kah Kheng Lim, Carlos Angulo–Preckler, Christopher A. Hempel, Mohammad A. Qurban, Vincent A. Pieribone, Carlos M. Duarte (2025). Benthic Feeding and Diet Partitioning in Red Sea Mesopelagic Fish Resolved Through DNA Metabarcoding and ROV Footage. , 15(3), DOI: https://doi.org/10.1002/ece3.71091.
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Type
Article
Year
2025
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1002/ece3.71091
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