Environmental and predator control of mysid shrimp vertical distribution in Lake Superior assessed from uncrewed surface vessels

Mysid shrimp (Mysis diluviana) are the dominant offshore zooplankton food item for planktivorous fish throughout Lake Superior. Understanding mysis vertical distribution throughout the lake is important for informing their habitat overlap with benthic and pelagic fish predators. We use active hydroacoustic data from two autonomous Uncrewed Surface Vessels (USV) collected in the western arm of Lake Superior from 11 August to 13 September 2022 to assess the vertical distribution of mysids and fish through several diel vertical migration (DVM) cycles. Low-noise data generated from USVs also made it possible to assess deep daytime mysid and fish distributions. Using satellite-derived surface light attenuation data and an astronomical surface illuminance model, we predicted the depths of mysids for both day and night using published mysid distribution models based on light and temperature preferences. We then used generalized additive models to compare USV-observed mysid depths with model-predicted mysid depths, and test for additional effects of fish depth and abundance. Surface light intensity and bathymetric depth significantly explained mysid depth both day and night. At night, mysid depth was further influenced by surface water temperature, fish depth, and fish biomass. Finally, during the day only fish depth further improved model fit. This enhanced view of mysid vertical distribution provides insight on trophic connectivity between fish and mysids as well as benthic-pelagic coupling in the offshore of Lake Superior.

Presentation Preference: Standard Oral (12 Minutes)

Primary Presenter: Kayden Nasworthy, Cornell University (kcn33@cornell.edu)

Authors:

Kayden Nasworthy, Cornell University  (kcn33@cornell.edu)

Thomas Evans, SUNY Brockport  (tevans@brockport.edu)

James Watkins, Cornell University  (jmw237@cornell.edu)

Suresh Sethi, Brooklyn College  (suresh.sethi@brooklyn.cuny.edu)

Daniel Yule, United States Geological Survey  (dyule@usgs.gov)

Peter Esselman, United States Geological Survey  (pesselman@usgs.gov)

Lars Rudstam, Cornell University  (lgr1@cornell.edu)