Characterizations of gelatinous zooplankton communities are necessary for an improved understanding of the ecological and temporal dynamics of such communities and their composing taxa. Yet, studies on gelatinous zooplankton communities are scarce in the Red Sea, which is characterized by extreme temperature, high salinity and oligotrophic conditions. Here, we analyzed the occurrence of gelatinous zooplankton taxa in a time-series of epipelagic samples taken from September 2016 to May 2018 in the central Red Sea to deliver the first complete characterization of gelatinous zooplankton in the Red Sea. General seasonal dynamics were found over the year, where higher gelatinous zooplankton abundances were relate to mostly with lower temperatures, lower salinity and to a lesser extent, with chlorophyll a, cross-shelf and along-shelf Ekman transport. Tunicates and siphonophores presented seasonal patterns, whereby total biovolume values were 103 – 105 higher in winter – early spring than in summer, and numbers > 100 higher in the bloom event of 2017/2018 than in 2016/2017. Ulmaridae (Aurelia sp.) peaked after the main bloom event of siphonophores and tunicates, and dominated total biovolume when present. Porpitidae was consistently present and showed no clear seasonality. Our results suggest that there is a noticeable seasonal trend in gelatinous zooplankton, marked by high occurrences in winter-early spring, very low occurrences over summer, and mostly dominated by Salpidae and Dyphidae. Porpitidae was a dominating group with non-seasonal occurrence, and Ulmaridae was also dominating but with very short and few occurrences. In addition, low abundance and biovolume (max. 8 ind m–3 and max. 103 – 106 mm3 m–3) suggest that oligotrophic conditions may be limiting the productivity of gelatinous zooplankton communities in the Red Sea.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank S. Haddock, G. Paulay, W. Patry, and C. E. Mills for identification advice, J. de la Cruz Martinez for sampling, and CMOR for facilities and assistance throughout the sampling. Funding. This research was funded by King Abdullah University of Science and Technology (KAUST) through baseline funding to SA and CD. JS was supported by KAUST through the VSRP Program.