Plant functional traits are quantifiable elements of ecological strategies. Studying them can thus offer insights into the ecological and evolutionary processes shaping natural plant communities. Despite evidence that leaf and root traits may coordinate or diverge at the species level, community-level root traits and strategies are often assumed to mirror those of aboveground traits in natural communities. Thus, belowground functional traits and their influence on community responses to environmental variation remain less well understood than their aboveground counterparts. This study addresses this knowledge gap by evaluating community above- and belowground resource-use strategies along biotic and abiotic environmental gradients in a diverse semi-arid annual plant system. Using specific leaf area (SLA) and specific root length (SRL) as comparable above- and belowground traits, we anticipated that plant communities would shift towards acquisitive strategies in both leaf and root trait values in resource-rich environments with mild climate conditions, aligning with the fast-slow plant economic spectrum. Our results show that community-level SLA and SRL align with the fast-slow economic spectrum along gradients of temperature, precipitation and canopy cover. Yet, community-level above- and belowground resource-use strategies are governed by different environmental factors. We found that maximum temperature most strongly predicted SLA, while precipitation was the strongest predictor of SRL at the community level. Above- and belowground community traits varied in their response direction and magnitude to the same environmental factors. While community-level SLA and SRL responded in a coordinated manner to remnant-level predictors, they diverged in response to micro-environmental variation. Our findings suggest that community-level above- and belowground traits reveal different but complementary community responses to the environment, highlighting the importance of incorporating root traits into ecological studies. Our results provide new insights into which plant traits are best suited to predicting annual plant community assembly under environmental change.