A combined morphological and DNA Barcoding approach for large-scale analysis of fish egg communities and its application in the seagrass bed-coral reef seascapes of eastern Hainan
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Graphical Abstract
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Abstract
This study analyzed the species composition and community structure of fish eggs in a specific seagrass bed–coral reef habitat in eastern Hainan, and evaluated its function as a spawning ground, providing valuable information for fisheries resource management and conservation. Fish eggs were identified using an integrative approach combining DNA barcoding and morphology. A workflow for determining species composition and abundance in large egg-sample datasets based on morphological–molecular integration was established: (1) fish eggs were assigned to distinct morphological groups and additional subgroups according to typical morphological characteristics and subtle differences; (2) each morphological group/subgroup was counted and subsampled, and each subsampled egg was photographed to record morphological traits and then molecularly sequenced to determine species identity. Species composition and abundance of the community were determined by integrating the above results. A total of 96 fish-egg samples (86 596 eggs) were collected from the nearshore seagrass bed–coral reef seascape off Wenchang, Hainan, during April–May 2024, and 20 morphological groups were delineated. COI sequences were successfully obtained from 1 208 eggs, identifying 66 species belonging to 8 orders, 29 families and 45 genera. Perciformes had the highest species richness (30 species, 45.5%), followed by Scorpaeniformes (13 species, 19.7%). Scorpaenidae contained the most species (11 species, 16.7%), followed by Labridae (8 species, 12.1%). The correspondence between morphological groups and taxonomic groups was further established. These results confirm the seagrass bed–coral reef seascape as an important spawning habitat for these fishes. This study provides a practical and scalable framework for community-level analyses of large fish-egg datasets, offering a robust methodological foundation for fisheries resource assessment and marine ecological conservation.
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