The leaf economics spectrum (LES) refers to a suite of correlated leaf-level physiological, morphological, and chemical traits that can be used to describe life-history strategy among plant species. Documenting LES trait variation across environmental gradients has been important for understanding natural plant community dynamics in response to environmental change. However few studies have examined how LES traits covary within crops, or how the LES is correlated with farm-level management practices or goals, especially for important tree-crops such as coffee. We analyzed within-species variation in eight leaf traits in 60 Coffea arabica plants, across four management treatments differing in shade-tree species composition, to test (i) if hypothesized LES patterns also describe within-species trait variation, and (ii) if LES traits vary in response to management regimes, or are correlated with reproductive output. Leaf traits varied widely across coffee plants with photosynthetic rates (Amass) and leaf area showing especially high variation. In bivariate and multivariate analyses, coffee leaf traits covaried in patterns consistent with the LES, suggesting shifts between leaf-level resource acquisition and conservation traits among plants may also underpin coffee responses to agroforestry management. The position of a coffee plant along the LES (as described by a principal component analysis score) was best explained by light availability, but did not vary systematically with shade tree composition. LES traits were weakly but significantly related to plant-level reproductive output: coffee plants associated with lower Amass and leaf N values, and higher leaf mass per area were associated with greater reproductive output. In showing that the LES describes resource capture and/or conservation strategies among coffee plants, our study represents a novel adoption of the LES to address applied questions in managed systems. Since within species differences in leaf traits partially explain differences in coffee yield, we also suggest that trait-based research in agroecology can contribute to an applied and comprehensive understanding of crop functional biology, and ultimately, agroecosystem structure and function.