SummaryTraits link observable patterns in plants to ecosystem functions and processes and help to derive general rules and predictions about responses to environmental gradients, global change and perturbations. Ecological field studies often use manual low-throughput methods to assess plant phenotypes and integrate species-specific traits to community-wide indices. In contrast, greenhouse or lab-based studies, mostly in agriculture, employ high-throughput phenotyping for plant individuals to track their growth or fertilizer and water demand. We customized an automated plant phenotyping system (PlantEye F500, Phenospex, Heerlen, The Netherlands) for its mobile application in the field for digital whole-community phenotyping (DWCP). By scanning whole plant communities, we gather, within seconds and non-invasively, multispectral and physiological information while simultaneously capturing the 3-dimensional structure of the vegetation. We demonstrated the potential of DWCP by tracking plant community responses to experimental land-use treatments over two years. DWCP captured short- and long-term changes in morphological and physiological plant community properties in response to mowing and fertilizer treatments and thus reliably informed about changes in land-use. In contrast, manually measured community-weighted mean traits and species composition remained largely unaffected and were not informative about these treatments. Thus, DWCP proved to be an efficient method to measure morphological and physiological characteristics of plant communities, complements other methods in trait-based ecology, provides indicators of ecosystem states, and may help to forecast tipping points in plant communities often associated with irreversible changes in ecosystems.