Identifying Relationships between Catches of Spawning Condition Yellow Perch and Environmental Variables in the Western Basin of Lake Erie

Although the reproductive behavior of yellow perch Perca flavescens has been well documented in small systems, relatively little is known about the spawning preferences of yellow perch in large systems, such as the Laurentian Great Lakes. During 2006 and 2007, we compared the presence and abundance adult yellow perch during the spring spawning season with environmental variables in the western basin of Lake Erie. We also estimated the timing of yellow perch spawning by comparing the relative abundance of gravid and spent females collected in our trawls and then comparing the proportion of gravid females with environmental conditions at our sampling sites. Overall, the probability of catching adult yellow perch and the catch per unit effort increased with increasing bottom temperatures in the spring, whereas the probability of catching gravid females increased with increasing Secchi depth. However, the relationships between our catch metrics and environmental variables were not consistent across years, possibly as a result of the very strong 2003 year‐class, which became first‐year spawners in 2006. We also documented that yellow perch spawning occurred when bottom temperatures were between 11°C and 15°C in the western basin; these temperatures were reached on different dates in different parts of the basin and in different years. Thus, we suggest that management agencies consider basing the start of the commercial fishing season on prevailing bottom temperatures rather than using a set date across years and sites.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142328/1/tafs0031.pd

Comparative Recruitment Dynamics of Alewife and Bloater in Lakes Michigan and Huron

The predictive power of recruitment models often relies on the identification and quantification of external variables, in addition to stock size. In theory, the identification of climatic, biotic, or demographic influences on reproductive success assists fisheries management by identifying factors that have a direct and reproducible influence on the population dynamics of a target species. More often, models are constructed as one‐time studies of a single population whose results are not revisited when further data become available. Here, we present results from stock recruitment models for Alewife Alosa pseudoharengus and Bloater Coregonus hoyi in Lakes Michigan and Huron. The factors that explain variation in Bloater recruitment were remarkably consistent across populations and with previous studies that found Bloater recruitment to be linked to population demographic patterns in Lake Michigan. Conversely, our models were poor predictors of Alewife recruitment in Lake Huron but did show some agreement with previously published models from Lake Michigan. Overall, our results suggest that external predictors of fish recruitment are difficult to discern using traditional fisheries models, and reproducing the results from previous studies may be difficult particularly at low population sizes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141414/1/tafs0294.pd

Reliability of Bioelectrical Impedance Analysis for Estimating Whole‐Fish Energy Density and Percent Lipids

We evaluated bioelectrical impedance analysis (BIA) as a nonlethal means of predicting energy density and percent lipids for three fish species: Yellow perch Perca flavescens, walleye Sander vitreus, and lake whitefish Coregonus clupeaformis. Although models that combined BIA measures with fish wet mass provided strong predictions of total energy, total lipids, and total dry mass for whole fish, including BIA provided only slightly better predictions than using fish mass alone. Regression models that used BIA measures to directly predict the energy density or percent lipids of whole fish were generally better than those using body mass alone (based on Akaike’s information criterion). However, the goodness of fit of models that used BIA measures varied widely across species and at best explained only slightly more than one‐half the variation observed in fish energy density or percent lipids. Models that combined BIA measures with body mass for prediction had the strongest correlations between predicted and observed energy density or percent lipids for a validation group of fish, but there were significant biases in these predictions. For example, the models underestimated energy density and percent lipids for lipid‐rich fish and overestimated energy density and percent lipids for lipid‐poor fish. A comparison of observed versus predicted whole‐fish energy densities and percent lipids demonstrated that models that incorporated BIA measures had lower maximum percent error than models without BIA measures in them, although the errors for the BIA models were still generally high (energy density: 15‐18%; percent lipids: 82‐89%). Considerable work is still required before BIA can provide reliable predictions of whole‐fish energy density and percent lipids, including understanding how temperature, electrode placement, and the variation in lipid distribution within a fish affect BIA measures.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141722/1/tafs1519.pd

Experimental and field evaluation of otolith strontium as a marker to discriminate between river-spawning populations of walleye in Lake Erie

Otolith microchemistry is a commonly used tool for stock discrimination in fisheries management. Two key questions remain with respect to its effectiveness in discriminating among river-spawning populations. First, do larvae remain in their natal river long enough for their otoliths to pick up that systemâ s characteristic chemical signature? Second, are larval otolith microchemical differences between natal rivers sufficiently large to overcome spatiotemporal variation in water chemistry? We quantified how larval age, the ratio of ambient strontium to calcium concentrations (Sr:Ca), and water temperature influence otolith Sr in both lab-reared and wild-collected Lake Erie walleye (Sander vitreus). Otolith microchemistry shows promise as a spawning stock discrimination tool, given that otolith Sr in larval walleye: 1) is more strongly influenced by ambient Sr:Ca than by temperature; 2) reflects Sr:Ca levels in the natal environment, even in larvae as young as 2 d; and 3) can effectively discriminate between larvae captured in two key Lake Erie spawning tributaries, even in the face of short larval river-residence times and within-year and across-year variation in ambient Sr:Ca.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Introduction to the special section: Status and approaches to assess Lake Erie Central Basin hypoxia

Seasonal hypolimnetic hypoxia has occurred in Lake Erie\u27s central basin since at least the 1950s. The 2012 Great Lakes Water Quality Agreement includes a lake ecosystem objective that commits Canada and the United States to minimize the extent of hypoxic zones, with a particular emphasis on Lake Erie. To meet that objective, Canada and the United States adopted a 40% total phosphorus load reduction target for the western and central basins of the lake. To help assess progress in minimizing Lake Erie\u27s hypoxic zones, the Cooperative Institute for Great Lakes Research (CIGLR) convened a virtual summit in October 2021 to update the state-of-knowledge regarding hypoxia in Lake Erie. This special section summarizes the recommendations for monitoring, assessment, modeling and reporting of hypoxia that resulted from the workshop and features five papers that present new information about hypoxia in Lake Erie. Recognizing that hypoxia occurs in other areas within the Great Lakes basin, a paper investigating seasonal drivers of hypoxia dynamics in Muskegon Lake a drowned river mouth that flows into Lake Michigan, is also featured