Minnesota macrophytes: linking aquatic plants, lake health, and human activities

Abstract

Aquatic plants (macrophytes) are an undervalued but critically important component of Minnesota's lakes. The macrophyte Index of Biotic Integrity (IBI) was developed to evaluate lake health using metrics that describe the condition of the aquatic plants. However, a detailed evaluation to determine whether the index can explicitly link lake condition with activities that negatively impact lake resources has not been conducted. This information is necessary before the IBI can be used to develop biological standards required under the federal Clean Water Act. The goal of this dissertation was to develop and implement a framework for identifying the strengths and weaknesses of the index to inform biological assessment. Four chapters describe research to fulfill this goal. The first chapter identifies comparable groups of lakes using a set of environmental variables that influence macrophyte community composition. The second chapter describes the development and application of semi-automated techniques for quantifying potential stressors of aquatic macrophytes in nearshore areas of lakes, such as docks and boat lifts. The third chapter provides a complementary analysis to chapter two by examining the relationships of shoreline development at different spatial scales with metrics describing macrophyte richness. The fourth and final chapter develops modeling techniques to quantify the relative effects of multiple stressors on the IBI. Specifically, I have used artificial neural network models that can 'learn' inherent data structures and are especially useful for modeling noisy data with non-linear relationships. Outcomes from my dissertation will inform management agencies on the most appropriate use of the index, which will ultimately facilitate the protection and restoration of Minnesota's lakes.