Recognized, well-covered traits are indispensable for large-scale analyses that provide syntheses explaining processes driving ecosystems worldwide (Chave et al., 2018;Madani et al., 2018;Niinemets et al., 2015). Yet, processes taking place at different levels of life organization cannot always be explained using the same functional traits (Lanta et al., 2011;Messier et al., 2010), because the factors driving ecological processes also differ across spatial scales (Pearson & Dawson, 2003). Therefore, we should move toward a more even coverage of the functional traits representing the diverse organs and biological functions of a plant (Cornwell et al., 2019;Kleyer & Minden, 2015). As a consequence, we could overlook and ignore other, perhaps highly explanative traits (Moravcová et al., 2015).Moreover, covering less-known traits with a higher number of measurements could reveal their hidden explanatory potential (Moravcová et al., 2015). Evenly covering different traits with measurements is the key to better-balanced models: As long as data are