ABSTRACT – RESEARCH PROJECT 3 The production and transport of cyanotoxins along the freshwater-to-marine continuum raises critical public health concerns, especially for coastal populations that are more likely to be exposed to contaminated water and seafood. Moreover, while cyanobacteria and cyanotoxins have been relatively well studied in freshwater lakes, little is known about their distribution and persistence in coastal systems. Thus, the overarching objective of Project 3, as an integral component of the North Carolina Center for Coastal Algae, People, and Environment (NC C-CAPE), is to develop a comprehensive modeling framework that elucidates key controls on toxin accumulation and provides predictive capabilities to help stakeholders protect human health. Through leveraging diverse data and information sources within a probabilistic framework (Bayesian Network modeling), Aim 1 of this research provides the predictive basis for estimating cyanotoxin risks from key environmental covariates, like temperature, salinity, nutrient concentrations, and solar radiation. The resulting models will enable prediction of cyanotoxin congener concentrations in water and oyster tissue, including the risk of exceeding health advisory thresholds, even when only a subset of relevant covariates is available. While Aim 1 is based largely on water quality data from specific monitoring locations, protecting public health requires a predictive understanding of how cyanotoxins vary across space and time. To this end, Aim 2 will leverage coastal circulation modeling and remote sensing to assess how key drivers of cyanobacteria and cyanotoxins vary across the coastal North Carolina study area. By combining this information with probabilistic relationships for cyanotoxin concentration (for example, the Bayesian Network from Aim 1), it will be possible to map toxin risks across space, and under different hydrological conditions. This effort will also allow us to determine the extent to which toxic cyanobacteria blooms are constrained to regions of freshwater inflow and transport (e.g., river outlets), versus forming in-place at various points along the freshwater-to-marine continuum. Finally, coastal systems are vulnerable to multiple dimensions of climate change, including sea level rise, increasing temperatures, and changes in freshwater inflow. These factors, along with potential changes in nutrient loading due to watershed development, will be investigated in the future scenarios of Aim 3. Aim 3 will update the modeling approach described in Aim 2 with future system forcings to assess future cyanotoxin distributions, including the likely overlap with viable oyster habitat. For each of the three aims, we will engage with stakeholders to develop relevant predictive tools and risk mapping products, with the aim of protecting public health by identifying high-risk conditions, and informing future management decisions regarding the protection of coastal water quality.