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Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species

May 13, 2021

Ecosystem-based management relies on understanding how perturbations influence ecosystem structure and function (e.g., invasive species, exploitation, abiotic changes). However, data on unimpacted systems are scarce; therefore, we often rely on impacted systems to make inferences about ‘natural states.’ Among the Laurentian Great Lakes, Lake Superior provides a unique case study to address non-native species impacts because the food web is dominated by native species. Additionally, Lake Superior is both vertically (benthic versus pelagic) and horizontally (nearshore versus offshore) structured by depth, providing an opportunity to compare the function of these sub-food webs. We developed an updated Lake Superior EcoPath model using data from the 2005/2006 lake-wide multi-agency surveys covering multiple trophic levels. We then compared trophic transfer efficiency (TTE) to previously published EcoPath models. Finally, we compared ecosystem function of the 2005/2006 ecosystem to that with non-native linkages removed and compared native versus non-native species-specific approximations of TTE and trophic flow. Lake Superior was relatively efficient (TTE = 0.14) compared to systems reported in a global review (average TTE = 0.09), and the microbial loop was highly efficient (TTE > 0.20). Non-native species represented a very small proportion (<0.01%) of total biomass and were generally more efficient and had higher trophic flow compared to native species. Our results provide valuable insight into the importance of the microbial loop and represent a baseline estimate of non-native species impacts on Lake Superior. Finally, this work is a starting point for further model development to predict future changes in the Lake Superior ecosystem.

Publication Year 2021
Title Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species
DOI 10.1016/j.jglr.2021.04.010
Authors Bryan G. Mathias, Thomas R. Hrabik, Joel C. Hoffman, Owen Gorman, Michael J. Seider, Michael E. Sierszen, Mark Vinson, Daniel Yule, Peder M. Yurista
Publication Type Article
Publication Subtype Journal Article
Series Title Journal of Great Lakes Research
Index ID 70220443
Record Source USGS Publications Warehouse
USGS Organization Great Lakes Science Center