The engineering of photosynthetic bioprocesses is associated with many hurdles due to limited mechanistic knowledge and inherent biological variability. Because of their ability to accumulate high amounts of beta-carotene, green microalgae of the Dunaliella genus are of high commercial relevance for the production of food, feed, and high-value fine chemicals. This work aims at investigating the interspecies differences between two industrially relevant Dunaliella species, namely D. salina and D. parva. A systematic work flow composed of experiments and mathematical modeling was developed and applied to both species. The approach combining flow cytometry and pulse amplitude modulation (PAM) fluorometry with biochemical methods enabled a coherent view on the metabolism during the adaptational stress response of Dunaliella under carotenogenic conditions. The experimental data was used to formulate a dynamic-kinetic reactor model that covered the effects of light and nutrient availability on biomass growth, internal nutrient status, and pigment fraction in the biomass. Profile likelihood analysis was performed to ensure the identifiability of the model parameters and to point out targets for model reduction. The experimental and computational results revealed significant variability between D. salina and D. parva in terms of morphology, biomass, and beta-carotene productivity as well as differences in photoacclimation and photoinhibition. The synergistic approach combining experimental and mathematical methods provides a systems-level understanding of the microalgal carotenogenesis under fluctuating environmental conditions and thereby drive the development of sustainable and economically feasible phototrophic processes.