Individual-based models (IBMs) are a promising avenue for predicting phytoplankton dynamics in lakes and reservoirs, as they can account for trait heterogeneity in individuals within a taxon as well as across taxa (e.g., cell or colony size, density, nutrient uptake rates etc.). However, IBMs are often coupled with complex, 3D lake hydrodynamic models and are computationally expensive to run. To facilitate use of IBMs within the ecological research community, we are developing approachable, open-source phytoplankton IBM models. These models are designed to minimize runtimes as well as provide the user with multiple options for representing phytoplankton processes within the model.

• phytoABM-R (in development): an 1D R-based phytoplankton individual-based model, with multiple options for representing temperature, light, and nutrient limitation on phytoplankton growth

• GLM-AED-IBM (in development): a 1D phytoplankton individual-based model fully coupled with the General Lake Model - Aquatic EcoDynamics (GLM-AED) model

This work is part of an NSF-sponsored project: Applying rules of life to forecast emergent behavior of phytoplankton and advance water quality management.