Navigating Lake Ontario coregonine restoration: Analysis of contemporary and future food web structures

Alex Koeberle, Tom Stewart, Rudstam, Suresh Sethi and Jim Watkins. (Funded by New York Sea Grant). Project collaborators: Tom Stewart, Marten Koops, Henrique Giacomini, Kevin McCann, Kayla Hale, Kevin Cazelles, Mike Yodzis

Restoring native species is believed to improve food web function and mitigate both invasive species disruption and declines in primary production. Yet, to our knowledge this has not been evaluated for Great Lakes ecosystems. Cisco (Coregonus artedi) restoration, for example, is used as a management tool across the Great Lakes basin to stabilize forage (mid-trophic level) fisheries and increase diversity of native fish community assemblages partly because restoring native fish is considered beneficial to food web function. In New York State this includes management actions to increase native coregonine populations in Lake Ontario and active reintroductions of the species in the Finger Lakes region. This study utilizes novel advances in food web modeling tools, Linear Inverse Modeling (LIM), to evaluate the structure and function of contemporary and possible future Lake Ontario food webs under two proposed scenarios: Contemporary food webs with present levels of coregonine populations, and future with restored complement of coregonine populations (shallow and deepwater species). To address this, our LIM food webs constrain lower-trophic compartments to observed levels of production ranges and only prescribe the topology and bioenergetics of fish species-groups, with no constraints on fish production. Our approach quantifies the potential multi-species landscape of mass-balanced future fish assemblages and examines tradeoffs between future levels of restored native and non-native fish species production. Because fish production is limited by lower-trophic level production, our approach is useful for quantifying restoration potential from a whole-ecosystem perspective. This research will advance food web analytics, food web theory, and fisheries management planning throughout the Great Lakes basin.