Phenotypic diversity within plant species is crucial to shaping evolutionary responses of populations and interactions among species, yet intraspecific genetic variability notably in roots has attracted little attention. Further, evidence for the root−shoot trait synchronisation remains inconclusive, narrowing our understanding of the role that belowground traits play in local adaptation. We applied broad 'top-to-toe' phenotyping to a model system whose native environmental conditions were simulated in experimental settings. Fifteen maternal families of Norway spruce Picea abies from southern Finland grew in six combinations of two simulated growing seasons and three soil treatments. We scored variation in 25 functional traits, including size, architecture and morphology of intact root systems, and shoot growth and phenology. Careful phenotyping of roots uncovered five trait dimensions, with root size, architecture and morphology forming the three largest axes of variation. Dimensions varied in their treatment responses. We observed among-family differences in all trait dimensions, marking substantial within-population genetic diversity. For example, average total root length varied almost twofold among families, but family × soil interactions indicated treatment-specific estimates of genetic variance. Mirroring root traits, phenotypic plasticity and genetic variation characterised shoot growth and phenology. In all, the complete phenotypic dataset yielded six trait dimensions, with assorted measures of root system and shoot size composing the main axis of variation. Although plastic and genetically variable, root architecture and morphology were not associated with shoot growth in any treatment. Also phenology and root-to-shoot ratio were detached from the primary axis of trait variability. Our results demonstrate that complex within-species patterns of trait covariation can be observed even locally and that phenotypic variation in independent trait dimensions reflecting divergent growth strategies is under genetic control. More accurate predictions of population and species responses to changes in the environment can be achieved when such intraspecific diversity is taken into account.