Quantifying how environmental factors control the growth of phytoplankton communities is essential for building a mechanistic understanding of global biogeochemical cycles and aquatic food web dynamics. The strong effects of temperature on population growth rate have inspired two frameworks—the Eppley curve and the metabolic theory of ecology—that produce different quantitative relationships and employ distinct statistical approaches. Reconciling these relationships is necessary to ensure the accuracy of ecosystem mod-els. In this paper, we develop ways to compare these frameworks, overcoming their methodological differ-ences. Then, analyzing an extensive dataset (textgreater 4200 growth rate measurements), we find that increases in population growth rate with temperature are consistent with metabolic theory, and weaker than previous estimates of the Eppley curve. A 108C temperature increase will increase growth rates by a factor of 1.53, rath-er than 1.88 as in previous studies of the Eppley curve. Size and functional group membership are also criti-cal. Population growth rates decrease with size, but much less strongly that metabolic theory predicts. The growth rates of different functional groups scale similarly with temperature, but some groups grow faster than others, independent of temperature. Our results reconcile the analytical methods of the Eppley curve and metabolic theory, demonstrate that metabolic theory's temperature-scaling predictions are more accu-rate, and provide new insights into the factors controlling phytoplankton growth. To avoid over-estimating the effects of temperature on primary productivity, the parameterization of ecosystem models should be revised.