Assessing Factors Contributing to Cyanobacteria Harmful Algal Blooms in U.S. Lakes

Cyanobacteria Harmful Algal Blooms (CHABs) in inland lakes have emerged as a major threat to water quality from both ecological and public health standpoints. Understanding the factors and processes driving CHAB occurrence is important in order to properly manage ensuring more favorable water quality outcomes. High water temperatures and nutrient loadings are known drivers of CHABs; however, the contribution of landscape variables and their interactions with these drivers remains relatively unstudied at a regional or national scale. This study assesses upstream landscape variables that may contribute to or obstruct/delay nutrient loadings to freshwater systems in several hundred inland lakes in the Upper Mid-western and Northeastern United States. We employ multiple linear regression and random forest modeling to determine which variables contribute most strongly to CHAB occurrence. This lakeshed-based approach will rank the impact of each landscape variable on cyanobacteria levels derived from satellite remotely sensed data from the Medium Resolution Imaging Spectrometer (MERIS) sensor for the 2011 bloom season (July - October).