Abstract
Predicting ecosystem function from environmental conditions is a central goal of ecosystem ecology. However, many traditional ecosystem models are tailored for specific regions or ecosystem types, requiring several regional models to predict the same function. Alternatively, trait‐based approaches have been effectively used to predict community structure in both terrestrial and aquatic environments and ecosystem function in a limited number of terrestrial examples. Here, we test the efficacy of a trait‐based model in predicting gross primary production (GPP) in lake ecosystems. We incorporated data from >1000 United States lakes along with laboratory‐generated phytoplankton trait data to build a trait‐based model of GPP and then validated the model with GPP observations from a separate set of globally distributed lakes. The trait‐based model performed as well as or outperformed two ecosystem models both spatially and temporally, demonstrating the efficacy of trait‐based models for predicting ecosystem function over a range of environmental conditions.