摘要
Coral reefs support a wide range of organisms in the world,including jellyfish and their benthic relatives.However,quantifying the biodiversity of these organisms in reefs is a challenge because of their uneven distribution and cryptic early life stages,requiring the validation of alternative techniques for biodiversity assessment.Here,the biodiversity and spatial distribution patterns of jellyfish and their benthic relatives,from the Scyphozoa,Hydrozoa,and Ctenophora taxa(hereafter referred to as SHC),were investigated in the coral reefs of Xisha,China,using environmental DNA(eDNA)metabarcoding technology by collecting shallow seawater,mesophotic seawater,and sediment samples.One-hundred and eighty-eight SHC species spanning two phyla(Cnidaria and Ctenophora),three classes,11 orders,65 families,and 104 genera were identified,among which hydrozoans were the most dominant taxa,accounting for 89.81% of all SHC species.SHC species showed low connectivity between shallow and mesophotic habitats,presenting a clear vertical distribution pattern in coral reefs.In the mesophotic coral ecosystems(MCEs),140 SHC species(84.34%)were detected,of which 39.76% were exclusive to MCEs,with Zanclea sp.1,Orthopyxis integra,and Fabienna sphaerica being the dominant species.Additionally,although SHC diversity in seawater was higher than that in the sediment samples,22 species were identified only in the sediment samples,indicating that sediment eDNA may represent a valuable supplementary tool for the investigation of SHC communities in hot spots.In addition to revealing the vast diversity of SHC species occupying coral reef ecosystems in the Xisha Islands,our findings confirm the potential of eDNA metabarcoding as an advanced tool for monitoring the biodiversity of cryptic species.
基金
Supported by the National Science&Technology Fundamental Resources Investigation Program of China(No.2022FY100603)
the Key Project of the NSFC-Shandong Joint Fund(No.U2106208)
the National Key Research and Development Program of China(No.2023YFC3108200)
the Taishan Scholars Program(No.tsqn202211263)。
