Statistical error model comparison for logistic growth of green algae (Raphidocelis subcapitata)

Abstract We validate a model for the population dynamics, as they occur in a chemostat environment, of the green algae Raphidocelis subcapitata , a species that is often used as a primary food source in toxicity experiments for the fresh water crustacean Daphnia magna . We collected longitudinal data from 4 replicate population experiments with R. subcapitata . This data was fit to a logistic growth model to reveal patterns of the algae growth in a continuous culture. Overall, our results suggest that a proportional error statistical model is the most appropriate for logistic growth modeling of R. subcapitata continuous population growth.