Modeling the growth rates of cyanobacteria and diatoms in the Baltic Sea

Potential influences of various environmental factors on phytoplankton growth rates in the Baltic Sea are discussed. Our focus is on quantitative comparisons of growth rates of two phytoplankton functional types, diatoms and cyanobacteria. Growth rates are calculated as a function of quanta absorbed by phytoplankton. This in turn depends on phytoplankton exposition to light, which was simulated to represent realistic conditions encountered in the Baltic Sea in summer. In addition, phytoplankton absorption capability was characterized by absorption coefficients derived from measurements on phytoplankton mono-cultures isolated from the Baltic Sea. Estimated exposition of phytoplankton to photosynthetically available radiation (PAR) in surface waters can change about five times in case of the same solar surface insolation and water turbidity, solely due to changes in the mixed layer depth from 2 to 20 meters. When additionally changes in water turbidity are considered, phytoplankton PAR exposition can change by one order of magnitude. Light exposition and absorption properties of phytoplankton determine the effectiveness of light absorption. In our simulations for the same species of phytoplankton, changes in light exposition resulted in differences of an order of magnitude of absorbed quanta. The importance of accounting for absorptive properties is underlined through comparisons of the number of quanta absorbed by different phytoplankton types in the same environmental conditions. The effectiveness of light absorption translates to different growth rates achieved by each phytoplankton type. Our results support the notion that knowledge about phytoplankton absorption properties and light exposition is crucial when modeling phytoplankton in the Baltic Sea. Further progress is currently hindered by a lack of systematic information about maximum phytoplankton growth rates and their responses to specific environmental conditions for different functional types. Such information should be inferred in the future in specially designed laboratory experiments, that encompass realistic ranges of phytoplankton exposition to light, nutrients, temperatures and other conditions.

This work has been funded by the National Science Centre (contract number: 2017/25/B/ST10/00159 entitled: “Numerical simulations of biological-physical interactions and phytoplankton cycles in the Baltic Sea”) and by the statutory funds of IOPAN.