Flexible Classification of Wisconsin Lakes for Improved Fisheries Conservation and Management

Abstract

Successful fisheries management practices developed for one ecosystem can often be used in similar ecosystems. We developed a flexible lake classification framework in collaboration with ~100 fisheries biologists for improved fisheries conservation management in Wisconsin, USA. In total, 5,950 lakes were classified into 15 lake classes using a two‐tiered approach. In tier‐one, lakes were clustered into “simple” and “complex” sportfish assemblages. In tier‐two, lakes were further clustered using accumulated degree days, water clarity, and special cases. We focus on temperature and clarity because these factors often drive fisheries change over time—thus a lake's class can change over time. Lake class assignments were refined through a vetting process where fisheries biologists with expert knowledge provided feedback. Relative abundance, size‐structure, and growth rates of fishes varied significantly across classes. Biologists are encouraged to utilize class interquartile ranges in fisheries metrics to make improved fisheries assessments. We highlight hard‐won lessons from our effort including: (1) the importance of co‐developing classification frameworks alongside fisheries biologists; and (2) encouraging frameworks where lakes can shift classes and fisheries expectations over time due to factors like climate change and eutrophication.

Survival of a threatened salmon is linked to spatial variability in river conditions

“…Ecological classification frameworks are important tools for understanding the scaledependent processes that govern landscape patterns and organism responses (Wiens 2002;Higgins et al 2005;Rypel et al 2019). The FLAMe system provided an empirical method for delineating longitudinal heterogeneity at a scale that could be related to outmigration survival, thus providing ecological context to spatial patterns in mortality.…”

“…Beyond a telemetry application, this method may serve as a simple, fast way to identify geographic zones within which fisheries management policies or restoration projects could be implemented. Applications of classification tools are many and include improved setting of regional fisheries expectations, use in developing more effective fish stocking rates or harvest regulations, and improved design of scientific studies and monitoring efforts (Rypel et al 2019;Schupp 1992;Wehrly et al 2012). Managers could use a classification scheme based on regional patterns to set water quality and fisheries standards that balance human impacts and biological requirements, inform monitoring sites based on major change points within a river, and predict the impacts of land use and pollution controls.…”

Early evidence of natal‐habitat preference: Juvenile loons feed on natal‐like lakes after fledging

“…Juvenile loon preferences for large lakes are reflected in how prey resources vary across the lake classes used in this study (Rypel et al., 2019). The primary predictor of overall fish abundance is lake size; simple lakes are uniformly small and lack trophic diversity, whereas large complex lakes have high trophic diversity with maximum trophic levels of 4–5 (Rypel et al., 2019). While abundances of small fishes can be high in small lakes, they lack large calorically dense meals for loons, which may explain their limited preference for these lakes.…”

“…The Trophic Class dataset was based on studies of trophic lake communities in northern Wisconsin conducted by Rypel et al. (2019) and recognizes 12 types of lakes defined by discrete categorizations of trophic complexity (Complex => 4 sportfish species present; Simple =< 4 sportfish species), temperature (Warm or Cool), water clarity (Clear or Dark), and stratification dynamics (e.g., two‐story lakes exhibit significant vertical stratification such that both warm‐ and cold‐water fish communities are present within the same lake). As the Trophic Class dataset encompasses a wider spatial range than the Basic Lake Features dataset and contains water bodies that are not suitable for loons (i.e., rivers, trout ponds and lakes < 10 ha), we confined the Trophic Class dataset to overlap spatially with Loon Lake data and removed unsuitable water bodies.…”

Relative Effectiveness of D‐Frame Dip Nets, Quatrefoil Light Traps, and Towed Ichthyoplankton Nets for Larval Muskellunge

“…Study site.-Sampling was conducted during 2019 and 2020 in Snipe Lake, an 87-ha mesotrophic lake in Vilas County, Wisconsin. Snipe Lake is classified as a "complex-cool-clear" lake (Rypel et al 2019), indicating that it has at least four sport fish species, low growing degree-days, and a high Secchi depth. The primary sport fish assemblage in Snipe Lake consists of Muskellunge, Walleye Sander vitreus, and Smallmouth Bass Micropterus dolomieu.…”