The Sacramento-San Joaquin Delta (Delta) is experiencing an increase in the frequency and severity of Cyanobacterial Harmful Algal Blooms (CHABs), which can produce harmful cyanotoxins. This issue is likely to intensify due to climate changes and rising temperatures. The most common CHAB genus in the Delta is Microcystis. Currently, the most extensive dataset for tracking Delta CHABs is the Microcystis Visual Index (MVI), a qualitative assessment of Microcystis colony densities observed in surface water. This index, recorded by natural agency staff across numerous monitoring stations, provides broad spatial coverage but is inherently subjective and not quantitative, thereby limiting its utility.
This project has the following objectives: 1. Develop an MVI image classification model and model algorithm that can identify and quantify Microcystis aggregate presence and coverage level in digital photos. 2. Translate MVI rankings to Microcystis biomass ranges by obtaining data to ground-truth a range of Microcystis biomass that corresponds with MVI rankings 2 through 5. 3. Explore relationship between proportion of toxic Microcystis cells and Microcystis biomass levels by relating each MVI scale (for ranks 2 through 5) and Microcystis biomass range to a) proportion of toxic Microcystis cells (i.e. ratio of mcyE and 16S rDNA genes) and b) microcystin concentration, in surface grab samples.
