Evaluating Modeling Approaches for Phytoplankton Productivity in Estuaries

Phytoplankton comprise the base of the food web in estuaries and their biomass and rates of growth (productivity) exert a bottom-up control in pelagic ecosystems. Reliable means to quantify biomass and productivity are crucial for managing estuarine ecosystems. In many estuaries, direct productivity measurements are rare and instead are estimated with biomass-based models. A seminal example of this is a light utilization model (LUM) used to predict productivity in the San Francisco Estuary and Delta (SFED) from long timeseries data using an efficiency factor, ψ. Applications of the LUM in the SFED, Chesapeake Bay, and the Dutch Scheldt Estuary highlight significant interannual and regional variability, indicating the model must be recalibrated often. The objectives of this study are to revisit the LUM approach in the SFED and assess a chlorophyll-a to carbon model (CCM) that produces a tuning parameter, Ω. To assess the estimates of primary productivity resulting from the models, productivity was directly measured with a 13C-tracer at nine locations during 22 surveys using field-derived phytoplankton incubations between March and November of 2023. For this study, ψ was determined to be 0.42 ± 0.02 (r2 = 0.89, p < 0.001, CI95 = 319). Modeling productivity using an alternative CCM approach (Ω = 3.47 × 104 ± 1.7 × 103, r2 = 0.84, p < 0.001, CI95 = 375) compared well to the LUM approach, expanding the toolbox for estuarine researchers to cross-examine productivity models. One practical application of this study is that it confirms an observed decline in ψ, suggesting a decline in light utilization by phytoplankton in the SFED. This highlights the importance of occasionally recalibrating productivity models in estuaries and leveraging multiple modeling approaches to validate estimations before application in ecological management decision making.