Leveraging Public Data to Predict Global Niches and Distributions of Rhizostome Jellyfishes.

As climate change progresses rapidly, biodiversity declines, and ecosystems shift, it is becoming increasingly difficult to document dynamic populations, track fluctuations, and predict responses to climate change. Concurrently, publicly available databases and tools are improving scientific accessibility, increasing collaboration, and generating more data than ever before. One of the most successful projects is iNaturalist, an AI-driven social network doubling as a public database designed to allow citizen scientists to report personal biodiversity reports with accuracy. iNaturalist is especially useful for the research of rare, dangerous, and charismatic organisms, but requires better integration into the marine system. Despite their abundance and ecological relevance, there are few long-term, high-sample datasets for jellyfish, which makes management difficult. To provide some high-sample datasets and demonstrate the utility of publicly collected data, we synthesized two global datasets for ten genera of jellyfishes in the order Rhizostomeae containing 8412 curated datapoints from both iNaturalist (n = 7807) and the published literature (n = 605). We then used these reports in conjunction with publicly available environmental data to predict global niche partitioning and distributions. Initial niche models inferred that only two of ten genera have distinct niche spaces; however, the application of machine learning-based random forest models suggests genus-specific variation in the relevance of abiotic environmental variables used to predict jellyfish occurrence. Our approach to incorporating reports from the literature with iNaturalist data helped evaluate the quality of the models and, more importantly, the quality of the underlying data. We find that free, accessible online data is valuable, yet subject to biases through limited taxonomic, geographic, and environmental resolution. To improve data resolution, and in turn its informative power, we recommend increasing global participation through collaboration with experts, public figures, and hobbyists in underrepresented regions capable of implementing regionally coordinated projects.

Box Jellyfish Alatina alata Has a Circumtropical Distribution.

Species of the box jellyfish (Cubozoa) genus Alatina are notorious for their sting along the beaches of several localities of the Atlantic and Pacific. These species include Alatina alata on the Caribbean Island of Bonaire (the Netherlands), A. moseri in Hawaii, and A. mordens in Australia. Most cubozoans inhabit coastal waters, but Alatina is unusual in that specimens have also been collected in the open ocean at great depths. Alatina is notable in that populations form monthly aggregations for spermcast mating in conjunction with the lunar cycle. Nominal species are difficult to differentiate morphologically, and it has been unclear whether they are distinct or a single species with worldwide distribution. Here we report the results of a population genetic study, using nuclear and mitochondrial sequence data from four geographical localities. Our analyses revealed a general lack of geographic structure among Alatina populations, and slight though significant isolation by distance. These data corroborate morphological and behavioral similarities observed in the geographically disparate localities, and indicate the presence of a single, pantropically distributed species, Alatina alata. While repeated, human-mediated introductions of A. alata could explain the patterns we have observed, it seems more likely that genetic metapopulation cohesion is maintained via dispersal through the swimming medusa stage, and perhaps via dispersal of encysted planulae, which are described here for the first time in Alatina.

Phylogenomic Analyses Support Traditional Relationships within Cnidaria.

Cnidaria, the sister group to Bilateria, is a highly diverse group of animals in terms of morphology, lifecycles, ecology, and development. How this diversity originated and evolved is not well understood because phylogenetic relationships among major cnidarian lineages are unclear, and recent studies present contrasting phylogenetic hypotheses. Here, we use transcriptome data from 15 newly-sequenced species in combination with 26 publicly available genomes and transcriptomes to assess phylogenetic relationships among major cnidarian lineages. Phylogenetic analyses using different partition schemes and models of molecular evolution, as well as topology tests for alternative phylogenetic relationships, support the monophyly of Medusozoa, Anthozoa, Octocorallia, Hydrozoa, and a clade consisting of Staurozoa, Cubozoa, and Scyphozoa. Support for the monophyly of Hexacorallia is weak due to the equivocal position of Ceriantharia. Taken together, these results further resolve deep cnidarian relationships, largely support traditional phylogenetic views on relationships, and provide a historical framework for studying the evolutionary processes involved in one of the most ancient animal radiations.