AbstractsBusiness Management & Administration

Modeling the Impacts of Lake Level Control Structure Management Scenarios on Aquatic Vegetation Distributions in Higgins Lake, MIchigan

by Andrew Layman




Institution: University of Michigan
Department: Natural Resources and Environment
Degree: MS
Year: 2015
Keywords: Higgin's Lake; aquatic vegetation; lake management
Record ID: 2059475
Full text PDF: http://hdl.handle.net/2027.42/111002


Abstract

Initiated by riparian homeowners concerned with increased shoreline erosion due to artificially high managed lake levels, this study of the potential ecological impacts of changing lake level management strategies on Higgins Lake was funded by the Muskegon River Watershed Assembly via the Michigan Department of Natural Resource???s Fisheries Division Habitat Improvement Fund and the Higgins Lake Property Owners Association. The focus of this thesis was the development of bathymetric, substrate and vegetation maps from sonar surveys (conducted July-August, 2012) to assess the extents and distribution of submersed aquatic vegetation (SAV), a key component of fisheries habitat, and to develop a predictive model to quantify how changes to lake level management might impact those extents and distributions. The observed percent cover of SAV on Higgins Lake was 11.1% (approximately 1,138 acres) and was largely restricted to depths between 3 and 15 meters. The average observed depth of SAV was 6.03 m and the most frequent depth of SAV occurrence was 4.32 m; emergent vegetation was not observed during the survey. The maximum recorded height of SAV was 2.09 m. Average SAV height was 0.27 m (+/- 0.20 m) and the most frequently occurring SAV height was 0.13 m. The logistic regression model (R-squared = 0.397; covariates: depth, % light remaining at depth, slope and fetch) successfully predicted occurrence of SAV at a rate of 82.5% when compared to the observed data. The lake level management scenarios explored had a range of water surface elevations of 350.89 ??? 351.80 meters above mean sea level. Under these scenarios the predicted areal extent of SAV ranged from 1,276 acres at the lowest water surface elevation, to 1,416 acres at the highest. The baseline model scenario (same water surface elevation as during the survey) over-predicted SAV extents by 267 acres. The predicted depth range of SAV shifted in conjunction with changes to water surface elevation. Overall, the model did not predict significant changes to SAV extents or distributions under the lake level management scenarios in question and the potential changes are likely insufficient to measurably impact fisheries habitat on the lake.