Distribution and diversity of gelatinous zooplankton in the southern South China Sea

Although gelatinous zooplankton are widely distributed in many ocean ecosystems, they have been understudied due to their fragility nature, difficulties to sample or handle and a lack of expertise. This study gives an insight into the distribution and diversity of gelatinous species in the Southern South China Sea. Species composition, distribution and abundance of gelatinous zooplankton were investigated along the East Coast of Peninsular Malaysia. A total of 37 species were recorded from 10 locations along 4 transects at 5.10° N and 6.80° N extending from 103.2° E to 105.3° E in August 2016. Seven medusae, six siphonophores, four appendicularians, six chaetognaths, six salps, four doliolids and four pteropods were identified from the study area. Appendicularia with 201 ind/m3 was found to be the most dominant taxa recorded, followed by chaetognaths with 197 ind/m3. Scyphomedusae were the least represented group in the study, with an abundance of 8 ind/m3. Stations near the inshore region show higher abundance and diversity of gelatinous zooplankton compared to offshore regions. The evenness index between stations revealed that the gelatinous zooplankton were evenly distributed. According to Principal Component Analysis (PCA), the diversity and distribution of gelatinous zooplankton are driven by depth and temperature.

Pelagic tunicates (Appendicularia and Thaliacea) of Sri Lanka: two first records with an annotated checklist

In broadening the understanding of the diversity, distribution and seasonality of gelatinous zooplankton of Sri Lanka, a survey (‘Waya-jel-Survey’) was carried out in coastal waters of the country from 2016 to 2020, and the collected specimens of pelagic tunicates were taxonomically identified. Further, a comprehensive literature survey was conducted and the previous records on the occurrences of pelagic tunicates within the exclusive economic zone of Sri Lanka were cross-checked and listed in developing the first-ever annotated checklist. Among the samples collected in this study, Pyrostremma spinosum and Thalia sibogae were reported for the first time from Sri Lankan waters while two more thaliaceans, i.e., Doliolum denticulatum and Pegea confoederata, and six appendicularians, i.e., Fritillaria borealis sargassi, F. formica digitata, Oikopleura cophocerca, O. fusiformis, O. longicauda, and O. rufescens were re-recorded. In total, forty species (including two subspecies) in 19 genera, belonging to five families from four orders of the classes Appendicularia (n = 17 species) and Thaliacea (n = 23 species) were reported to be inhabited in Sri Lankan waters. Most of the records were from the Laccadive Sea region while the majority of the species have been reported during the northwest monsoon (December to February) period.

Salpivory by Colonial Reef Corals at Curaçao, Southern Caribbean

Salps (Phylum Tunicata, Family Salpidae) are transparent, gelatinous zooplankton that may occur in large densities (swarms) in the open ocean, where they form a food source for a variety of predators [...]

Life beneath the ice: jellyfish and ctenophores from the Ross Sea, Antarctica, with an image-based training set for machine learning

Southern Ocean ecosystems are currently experiencing increased environmental changes and anthropogenic pressures, urging scientists to report on their biodiversity and biogeography. Two major taxonomically diverse and trophically important gelatinous zooplankton groups that have, however, stayed largely understudied until now are the cnidarian jellyfish and ctenophores. This data scarcity is predominantly due to many of these fragile, soft-bodied organisms being easily fragmented and/or destroyed with traditional net sampling methods. Progress in alternative survey methods including, for instance, optics-based methods is slowly starting to overcome these obstacles. As video annotation by human observers is both time-consuming and financially costly, machine-learning techniques should be developed for the analysis of in situ /in aqua image-based datasets. This requires taxonomically accurate training sets for correct species identification and the present paper is the first to provide such data. In this study, we twice conducted three week-long in situ optics-based surveys of jellyfish and ctenophores found under the ice in the McMurdo Sound, Antarctica. Our study constitutes the first optics-based survey of gelatinous zooplankton in the Ross Sea and the first study to use in situ / in aqua observations to describe taxonomic and some trophic and behavioural characteristics of gelatinous zooplankton from the Southern Ocean. Despite the small geographic and temporal scales of our study, we provided new undescribed morphological traits for all observed gelatinous zooplankton species (eight cnidarian and four ctenophore species). Three ctenophores and one leptomedusa likely represent undescribed species. Furthermore, along with the photography and videography, we prepared a Common Objects in Context (COCO) dataset, so that this study is the first to provide a taxonomist-ratified image training set for future machine-learning algorithm development concerning Southern Ocean gelatinous zooplankton species.