Environmental triggers and modulators of mixotrophy in aquatic protists

Mixotrophy-the combined use of photosynthesis and phagotrophy within a single organism-is increasingly recognized as a dominant nutritional strategy among marine protists, profoundly influencing planktonic food webs and global biogeochemical cycles. Yet, predicting the balance between these two trophic modes remains challenging due to highly variable, dynamic responses across different taxa. Here, I synthesize experimental, physiological, transcriptomic, and modeling evidence to elucidate the environmental triggers (light, nutrients, temperature, and prey, among others) that govern mixotrophic behavior. I demonstrate that functional classification provides a stronger predictive framework than taxonomy alone. Specifically, constitutive mixotrophs (possessing innate plastids) typically exhibit tightly coordinated regulation of both trophic modes across environmental gradients. Conversely, non-constitutive mixotrophs (relying on prey-derived plastids) display greater metabolic decoupling and flexibility, often substituting one nutritional mode for the other. Across diverse lineages, nutrient limitation consistently emerges as the primary driver of phagotrophic allocation, highlighting mixotrophy's central role in maintaining stoichiometric balance under resource imbalance. In contrast, light intensity modulates rather than directly induces feeding, typically producing non-monotonic responses in which integrated phototrophic-phagotrophic performance peaks at intermediate irradiances rather than varying linearly with light availability. Furthermore, temperature acts primarily as a taxon-specific metabolic modulator, while prey availability and quality dictate cellular investment in photosynthetic machinery. Because multi-factor interactions dominate single-driver effects in natural environments, predicting mixotrophic responses requires bridging molecular regulatory mechanisms with ecological patterns. Ultimately, this synthesis highlights the critical need to incorporate functional-type distinctions into trait-based ecosystem models to accurately forecast plankton dynamics in a changing ocean.