Sets of photosynthesis-irradiance (P-I) curves yield more information about community photosynthesis when analyzed with proper models in mind. Based on ecosystem-specific considerations regarding the factors that explain spatial and temporal patterns of photosynthesis, theWebb model of photosynthesis can be extended and fitted to P-I data. We propose a method based on a series of nested models of increasing complexity to test whether supposed effects of environmental factors are reflected in the P-I data, whether more complex models fit the data significantly better than more simple models, and whether parameters describing the presumed dependencies can be estimated from the data set. We compare a direct approach, fitting the extended model to all P-I data at once, with a two-step approach in which photosynthetic efficiencies and maximum photosynthetic rates of individual P-I curves are determined first, and then related to environmental variables. A nested model approach prevents overfitting of multiparameter models. Monte Carlo analysis sheds light on the error structure of the model, by separating parameter and model uncertainty, and provides an assessment of the performance of the formulations used in ecosystem models. We demonstrate that the two-step approach underperforms when used to compute photosynthetic rates. We apply the proposed method to an extensive P-I data set from the Schelde estuary, where spatiotemporal patterns of photosynthesis arise from a combination of seasonality, silica depletion, phytoplankton community composition, and salinity effects.