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Jellyfish venoms are rich sources of toxins designed to capture prey or deter predators, but they can also elicit harmful effects in humans. In this study, an integrated transcriptomic and proteomic approach was used to identify putative toxins and their potential role in the venom of the scyphozoan jellyfish Chrysaora fuscescens. A de novo tentacle transcriptome, containing more than 23,000 contigs, was constructed and used in proteomic analysis of C. fuscescens venom to identify potential toxins. From a total of 163 proteins identified in the venom proteome, 27 were classified as putative toxins and grouped into six protein families: proteinases, venom allergens, C-type lectins, pore-forming toxins, glycoside hydrolases and enzyme inhibitors. Other putative toxins identified in the transcriptome, but not the proteome, included additional proteinases as well as lipases and deoxyribonucleases. Sequence analysis also revealed the presence of ShKT domains in two putative venom proteins from the proteome and an additional 15 from the transcriptome, suggesting potential ion channel blockade or modulatory activities. Comparison of these potential toxins to those from other cnidarians provided insight into their possible roles in C. fuscescens venom and an overview of the diversity of potential toxin families in cnidarian venoms.

As in many regions of the world, the shelf waters of the western United States have experienced large increases and high interannual variability in jellyfish populations in recent decades. The northern California Current (NCC) is a productive upwelling zone that is home to large populations of medusae, particularly during some years. Seasonal trawl surveys in the NCC over 13 yr have documented a substantial biomass of jellyfish consisting primarily of one species, the sea nettle Chrysaora fuscescens, with abundances generally peaking in late summer. Trophic overlap can be high in the NCC with planktivorous species such as Pacific sardines and herring that consume copepods and other zooplankton. In this study, we examine the spatial overlap and co-occurrence of C. fuscescens and Pacific herring Clupea pallasii, northern anchovy Engraulis mordax and Pacific sardine Sardinops sagax in the NCC using spatial analysis tools to determine the species that have the potential to be most affected by high jellyfish biomass and the geographic areas in which these interactions are likely to occur. Significant spatial overlap of C. fuscescens with these pelagic fishes occurred during certain months and years, although the results were highly variable. There was an overall negative relationship between the abundance of C. fuscescens and the catch of the 3 forage fishes for both June and September. End-to-end food web models show that jellyfish have a greater potential to affect production of pelagic forage fishes than the reverse.

Blooms of jellyfish around the world have been correlated with climatic variables related to environmental causes. Sizeable populations of large medusae, primarily Chrysaora fuscescens and Aequorea sp., appear annually in shelf waters of the Northeast Pacific Ocean. Previous research has shown that C. fuscescens is abundant seasonally in the inner shelf and exhibits high feeding rates on zooplankton. We examined medusae caught in surface trawls over an 8-year period (2000–2007) using (1) mesoscale surveys sampling 8–10 transects in May, June, and September, and (2) biweekly surveys along two transects from April to August, relating abundance to environmental parameters. C. fuscescens abundances generally peaked in late summer, whereas Aequorea sp. peaked in May or June. General additive models of the mesoscale data indicated that station catches for both species correlated with latitude, temperature, salinity, and distance from shore (and chlorophyll a for Aequorea sp.). Analysis of interannual variability revealed that highest catches of medusae correlated with cool spring–summer conditions, or negative anomalies of the Pacific Decadal Oscillation, and low winter–summer runoff from the Columbia River. Results confirmed our hypothesis of connections between jellyfish populations and regional climate conditions in a region known for strong physical forcing of ecosystem processes.

Interannual variability in salmon (Oncorhynchus spp.) production in the northeast Pacific is understood to be driven by oceanographic variability and bottom‐up processes affecting prey availability to juvenile salmon. Scyphozoan jellyfish have an important role in shaping the pathways of energy flow through pelagic food webs. While jellyfish obtain high production rates and biomasses as major consumers of zooplankton production, they have few predators and may divert plankton production away from higher trophic levels. Although jellyfish are planktivorous and juvenile coho (O. kisutch) and Chinook (O. tshawytscha) salmon are mainly piscivorous, they may be indirect competitors for plankton production. Ecosystem model simulations suggested that among all trophic interactions within the Pacific Northwest coastal food web, juvenile salmon are particularly sensitive to jellyfish blooms, and that salmon production will be suppressed in years of high summer jellyfish biomass. Pelagic surveys off Oregon and Washington (1999–2012) were used to examine the interannual relationship between salmon production and the dominant jellyfish species, the sea nettle Chrysaora fuscescens, off the Pacific Northwest coast. There was a significant, negative correlation between sea nettle biomass and the strength of adult coho and Chinook salmon returns to the Columbia River. Examination of spatial distributions across years showed a positive association between sea nettles and salmon. Within individual years, significant differences between the distribution of sea nettles and yearling coho and Chinook salmon generally occurred during cooler ocean summers, perhaps due to the greater expanse of optimal salmon habitat resulting from more upwelling. Whether the association is behavioral or a product of oceanographic processes, association enhances the opportunity for indirect competition. Examination of feeding incidence in September showed that salmon stomachs were less full at locations with higher sea nettle biomass.

We quantified diet and predation rates for large scyphomedusae from a coastal upwelling region. In the Northern California Current, early stages of euphausiids, gelatinous taxa, and cladocerans were particularly vulnerable to predation byChrysaora fuscescens,Aurelia labiata, andPhacellophora camtschatica, whereas copepods were not. Moreover,C. fuscescenshad the potential to deplete the standing stock of euphausiid eggs where predator and prey overlapped. During August 2002,C. fuscescensingested an average 32.5% of the standing stock of euphausiid eggs each day at stations close to shore and north of Cape Blanco (42.9° N, 126.6° W) where maximum abundances of the medusae occurred. Ingestion of other vulnerable prey, such as other early stages of euphausiids and gelatinous taxa, reached 10 to 12% d–1. In contrast, we calculated the maximum removal rate of the standing stock of copepods to be <1% d–1. Given the importance of euphausiids to fish and other top predators, and the potential for changes in abundance and distribution of both predator and prey taxa with changes in climate, we suggest that gelatinous zooplankton abundance and predation impacts be incorporated within long-term studies and ecosystem models.

The life cycle of the Northeast Pacific sea nettle, Chrysaora fuscescens Brandt, 1835, is described from gametes to the juvenile medusa stage. In vitro techniques were used to fertilize eggs from field-collected medusae. Ciliated planula larvae swam, settled, and metamorphosed into scyphistomae. Scyphistomae reproduced asexually through podocysts and produced ephyrae by undergoing strobilation. The benthic life history stages of C. fuscescens are compared with benthic life stages of two sympatric species, and a key to sympatric scyphomedusa ephyrae is included. All observations were based on specimens maintained at the Monterey Bay Aquarium jelly laboratory, Monterey, California.

On 2 December 2006, a heavy infestation of the parasitic hyperiid amphipods Hyperia medusarum and Lestrigonus shoemakeri was discovered in the sea nettles (Chrysaora fuscescens) exhibit at the Tennessee Aquarium. Pretreatment trials that exposed moon jellyfish (Aurelia aurita) and sea nettles to therapeutic levels of diflubenzuron confirmed that the treatment would be tolerated by these species of jellyfish. The exhibit tank was dosed with a 0.03 mg/L concentration of diflubenzuron for 7 days, after which the medication was removed by filtration. An arbitrarily chosen subset from the sea nettle exhibit was sampled regularly over the next 8 wk to monitor the parasite population. The average number of amphipods per jellyfish sampled decreased throughout the treatment and sampling period. No live amphipods were observed 6 wk after the start of treatment, and no negative side effects were observed in the sea nettles. The use of diflubenzuron to eradicate hyperiid parasites from scyphomedusae is a safe and useful option when properly applied in a controlled environment.

Zooplankton occupy critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood due to the difficulty of studying individuals in situ. Here we combine biologging with supervised machine learning (ML) to demonstrate a pipeline for studying in situ behavior of larger zooplankton such as jellyfish. We deployed the ITAG, a biologging package with high-resolution motion sensors designed for soft-bodied invertebrates, on 8 Chrysaora fuscescens in Monterey Bay, using the tether method for retrieval. Using simultaneous video footage of the tagged jellyfish, we develop ML methods to 1) identify periods of tag data corrupted by the tether method, which may have compromised prior research findings, and 2) classify jellyfish behaviors. Our tools provide characterizations of fine-scale jellyfish activity and orientation over long durations, and provide evidence that developing behavioral classifiers on in situ rather than laboratory data is essential.