The fitness of wild populations is ultimately determined by the simultaneous interaction of multiple environmental factors, yet the majority of ecological studies focus on a single driver or oversimplify these inherently complex relationships. Freshwater phytoplankton, for example, have been the focal organism for many mechanistic studies that have shown that, as isolated environmental factors, temperature and light are key in regulating population growth within freshwater ecosystems. However, a framework for understanding how these factors interact to influence phytoplankton growth and population dynamics is currently lacking. The primary goals of our current study are to (1) better understand how temperature-light interactions influence phytoplankton population growth and (2) determine the extent to which such interactions might play a meaningful role in accurately estimating the growth of phytoplankton in freshwater ecosystems. To these ends, we manipulated both temperature (9 levels from 12-40°C) and light intensity (6 levels from 6-600 µmol m-2 s-1) and monitored the population growth of 3 species of freshwater algae (Chlamydomonas reinhardtii , Chlorella vulgaris, and Cryptomonas ovata) in response to these 54 unique environmental combinations.
Results/Conclusions
Our results indicate that temperature and light strongly interact to influence phytoplankton population growth (i.e. fitness). We observed a range of growth rates from -0.692 to 4.095 /day, including environmental conditions that were above and below the optimal light (Iopt) and optimal temperature (Topt) values. Relative to expectations that predict phytoplankton fitness as a multiplicative outcome of temperature- and light-dependent processes, our results indicate that environmental temperature influences the Iopt, and that environmental light levels influence Topt. For example, in C. reinhardtii, the optimal temperature at 122.4 µmol m-2 s-1 was 29.6°C but 25.7°C for 501.8 µmol m-2 s-1. We also observed species-specific patterns in the range of light and temperatures tolerated as well as their interactive effects. Finally, by comparing light and temperature field data to estimates of fitness based on hypothetical scenarios displaying varying light-temperature interactions, we demonstrate that accounting for such interactions can substantially alter estimates of fitness. While our study provides a complementary analysis, overall, understanding the simultaneous impact of multiple ecological factors, and developing experimentally tractable approaches for resolving such complexity, remains a critical challenge field-wide.