Remotely sensed cyanobacterial intensity predicts likelihood of lake blooms and toxins across the contiguous US
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Cyanobacterial harmful algal blooms (CHABs) can produce toxins that impair freshwater ecosystems used for drinking water, recreation, and habitat for aquatic biota. With CHABs increasing in extent and intensity globally, water managers need information about how to prioritize lake monitoring. We combined the Cyanobacterial Assessment Network (CyAN) remote sensing data with the U.S. EPA National Lakes Assessments completed in 2007 and 2012 to predict the likelihood of measuring CHABs in lakes across the U.S. We use logistic regression modeling to relate the likelihood of lakes exceeding health recommendation thresholds associated with CHABs based on summer bloom intensity as measured by CyAN. We then used the model to extrapolate the likelihood of exceeding risk thresholds to all lakes monitored via CyAN. We find that the interannual mean bloom intensity from CyAN can be used to estimate the relative risk of lakes exceeding thresholds for cyanobacteria cell density, microcystin, and chlorophyll a during the period of 2007-2012. Such information can help inform setting priorities for lake water monitoring in regional contexts.