Ecosystems are warming alongside shifts in other abiotic factors, leading to interactive effects on populations and communities. This underscores the importance of studying how organisms respond to multiple environmental changes simultaneously. In pelagic ecosystems, as surface waters warm, longer and stronger periods of thermal stratification lead to changes in resource (light and nutrient) availability. We investigate the combined effects of temperature and resource availability on the growth rates of 19 populations (comprising 17 species) of freshwater phytoplankton in order to examine how temperature influences the minimum resource requirements (and Monod parameters) for light, nitrogen, and phosphorus. We also evaluate how resource availability affects each population's thermal traits (i.e., thermal performance curve - TPC - parameters). When averaged across all populations, the requirements for light and phosphorus tended to display a U-shaped relationship along temperatures. Individual populations varied greatly in their responses to temperature, leading to shifts in the identity of the best competitor across the thermal gradient, particularly for nitrogen and phosphorus. TPC responses to resource limitation were highly variable, but thermal optima and maxima of individual populations often decreased with resource limitation, and thermal breadths (range where growth is 80% or more of its maximum) often increased due to a flattening of TPCs. Across all populations and resource types, the maximum optimum temperature across resource levels (maximum T_opt ) tended to be positively correlated with the temperature at which populations had the lowest resource requirements (minimum R*). However, the temperature at which populations were the best competitors tended to be ~5°C colder on average than the temperature at which they grew the fastest. The populations with the highest thermal optima also had the lowest minimum resource requirements. Our findings reveal trait associations suggesting that some taxa already exhibit trait combinations that would support high performance under future warm and resource-limited conditions.