Clarifying larval Cisco and Lake Whitefish spatial ecology across habitat gradients to support evaluation, restoration, and management

Andrew Honsey (USGS, ahonsey@usgs.gov), Taylor Brown (Cornell), Ralph Tingley (USGS), Brian Weidel (USGS), Cory Brant (USGS), Robin DeBruyne (USGS), Nicole Watson (USGS), Gary Michaud (Little Traverse Bay Bands of Odawa Indians), Erin Dunlop (OMNR), Jose Bonilla-Gomez (USFWS)

Standardized early life monitoring programs for Cisco (Coregonus artedi) and Lake Whitefish (C. clupeaformis) are needed to evaluate outcomes of restoration interventions (Bunnell et al. 2023), but designing surveys that effectively sample each species ultimately depends on understanding their spatial ecology and habitat use (Cooke et al. 2016). A previously funded project, “Development of conceptual early life history models and evaluation of sampling techniques in support of long-term monitoring for Cisco and Lake Whitefish,” (PI R. Tingley) organized a multi-faceted workshop to build conceptual models of Cisco and Lake Whitefish early life history, suggest best sampling methods, and refine understanding of mechanisms underlying survival. The larval life stage is of particular interest for monitoring because larval dynamics (e.g., density, growth) can be used to investigate drivers of recruitment variability (e.g., Cunningham and Dunlop 2023) and evaluate restoration outcomes (e.g., detecting wild reproduction) over space and time (e.g., Pritt et al. 2015). However, participants felt unable to recommend appropriate sampling methods for larvae due to key uncertainties related to habitat use between species, among lakes, and through time. Workshop outcomes recommended the aggregation and analysis of existing larval Cisco and Lake Whitefish datasets to clarify spatial distributions across habitat gradients to inform monitoring program designs. Conceptual models developed during the workshop based on the literature and expert opinion indicate that Cisco and Lake Whitefish larval habitat use differs among lakes, suggesting that monitoring programs may need to differ in where and how they sample among lakes to effectively target larvae. Larval monitoring programs are unlikely to effectively sample both species simultaneously in Lake Superior, where Cisco are widely distributed offshore across bathymetric depths but Lake Whitefish are narrowly distributed in nearshore, shallow waters. In contrast, workshop participants generally agreed that larval monitoring programs in the other Great Lakes could effectively sample both species because larval Cisco and Lake Whitefish habitats often overlap. However, the extent to which they overlap across space and time remains uncertain, with Lake Whitefish generally being more nearshore and shallower than Cisco. Population assessments may be biased if sampling strategies systematically exclude portions of the distribution of one or both species. Additional research to quantify the degree to which observed larval habitat use differs among lakes and elucidate the mechanisms underlying these differences (e.g., ecological, geomorphological) is needed to inform larval sampling designs. While larvae of both species are generally found at highest densities at shallower depths and closer to shore—with Lake Superior Cisco being the sole exception—habitat geomorphology appears to be an important determinant of observed habitat use. Larval distributions in large and/or enclosed embayments sheltered from main lake conditions exhibit similar patterns across lakes. Specifically, larvae are found widely distributed across available habitats (i.e., bathymetric depth and distance from shore) in these embayments, including Green Bay (Ransom et al. 2022), several Lake Ontario embayments (Brown et al. 2023), and, arguably, the western basin of Lake Erie (Amidon et al. 2024). Because these habitats are relatively warm, productive, and low in fetch compared to the main lake, they may serve as high-quality nursery areas. Conversely, larvae occupying habitats more exposed to main lake conditions are found more restricted to the immediate nearshore; for example, open bays prevalent along the shorelines of lakes Michigan (Frederick 1982) and Huron (Overdyk 2015). In Lake Superior, Lake Whitefish may be better retained in nearshore nursery areas compared to Cisco larvae, which upon emergence offshore are susceptible to advection (Oyadomari and Auer 2008). Furthermore, island complexes (e.g., Apostle Islands, Fox and Grenadier Islands) represent yet another dimension of suitable larval habitat (Lachance et al. 2021; Brown et al. 2022). A holistic assessment of cross-basin larval habitat use is needed to clarify species-specific spatial ecology. Larval sampling strategies are further complicated by ontogenetic habitat shifts and changing susceptibility to sampling gears. Larvae migrate into nearshore areas within a few days to two weeks following emergence (Hart 1931; Pritchard 1931; Faber 1970; Brown et al. 2023). Larval swimming speeds increase with body size, along with their ability to actively maintain their position and avoid sampling gears (Miller et al. 1988). Surface trawls (e.g., neuston nets) are effective for sampling larval Cisco and Lake Whitefish generally less than 20 mm total length but alternative gears (e.g., beach seines) are needed to sample larger larvae (e.g., Pothoven 2025). Importantly, because larval Cisco typically hatch later and at a smaller size than Lake Whitefish, both species may not simultaneously occupy the same habitats or be susceptible to the same gears (Brown et al. 2023). For these reasons, it is possible that repeated sampling through time and space with multiple gears is needed to effectively sample larvae of each species. We propose to synthesize existing data to characterize larval Cisco and Lake Whitefish multidimensional habitat use across lakes and through ontogeny using spatial distribution modeling. This project will directly leverage larval data from previously funded proposals and the outcomes of the 2023 Great Lakes Cisco and Lake Whitefish Early Life Stage Workshop to fill critical knowledge gaps identified therein. This work is well suited to use the growing number of contemporary larval datasets using genetic identification which will strengthen our inferences of species-specific spatial ecology. Our results will inform sampling strategies for larval Cisco and Lake Whitefish monitoring programs by deepening understanding of characteristics associated with larval habitat among lakes and through ontogeny.