In this work a model of algal primary productivity combining a mechanistic light function with a temperature Arrhenius function is presented.Data on primary productivity obtained with algae acclimated to different environmental conditions was used to test the model. A simple method for model parameter estimation based on regression analysis is described. The parameter estimates can be improved by a non-linear least-squares method (e.g. the Gauss-Newton method) resulting in a significant fit to the observed data as tested by regression analysis.According to the present model, the initial slope of the productivity/light curves is temperature dependent whilst the optimal light intensity is temperature independent. These model predictions were validated by the obtained experimental results.