Application of Bayesian network inference algorithms for foodweb analysis: evaluating the impact of jellyfish predation on Irish Sea plankton

Jellyfish (pelagic meduasea of Cnidaria) are voracious plankton predators that can play major roles in structuring pelagic (water-column) marine ecosystems, but aspects of their ecology remain poorly described because of difficulties associated with sampling them using traditional netting techniques. We propose using recently-developed acoustic techniques (multi-frequency scientific echsounding) to estimate abundance of a guild of jellyfish (the Barrel jellyfish, Rhizostoma octopus; the Lion's mane jellyfish Cyanea spp.; the Sea nettle Chrysaora hysoscella, and the Moon jellyfish Aurelia aurita) in a region of the Irish Sea identified previously by aerial surveys as a Rhizostoma 'hot spot'. We will also sample non-gelatinous zooplankton (eg copepods, amphipods and fish larvae that are prey for jellyfish) using vertically-fished nets so that we can describe quantitatively the composition of the plankton (jellyfish 'food') under conditions of varying jellyfish abundance. We expect, in general terms, that there will be fewer zooplankton prey items in regions where jellyfish abundance is highest because jellyfish will have captured some zooplankton. Because there are numerous possible links in the foodweb via which zooplankton could be consumed (zooplankton may consume each other in addition to being consumed by jellyfish), we will apply powerful Bayesian network inference algorithms to multiple sets of regionally-naturally-varying jellyfish abundance and zooplankton abundance data to infer the most likely foodweb, and thus the impact by jellyfish on the plankton community. This will greatly improve our understanding of the predatory impact of jellyfish, and will provide insight to possible ecosystem consequences (eg to fisheries recruitment) of increasing jellyfish abundance following, for example, fishery-driven finfish decline or environmental change. It has been suggested that jellyfish will proliferate in the face of high fishing pressure because fishing removes fish that are competitors with jellyfish for plankton: less fish means more food for jellyfish. Once we have a robust foodweb model, we will use it in reverse with historic zooplankton abundance data (collected by the Continuous Plankton Recorder, a long-term zooplankton sampling programme run opportunistically from commercial ships) to reconstruct the likely changes over time in jellyfish abundance in the Irish Sea from the impact any changes in their abundance would have had on the zooplankton community. Herring stocks in the Irish Sea collapsed between 1972 and 1980 and, in a kind of ecological archaeology, we will look for clues in possible changing plankton community composition over that time for increases in jellyfish abundance. Although it has been suggested that jellyfish may proliferate following finfish decline (a consequence of so-called 'fishing down the foodweb') there is little direct evidence of this because time-series of jellyfish abundance are scarce (jellyfish do not have hard parts so, for example, leave little trace in sediments once they die). If we are able to reveal an historic link between jellyfish abundance and fish abundance this will be a very useful advance for managers seeking to regulate fisheries in an ecosystem context. The project will also demonstrate to a wide ecologist audience the power of inference algorithms for foodweb analysis.