Aim: China’s Grain for Green Program (GFGP) is the largest reforestation program in the world and has been operating since 1999. The GFGP has promoted the establishment of tree plantations over the restoration of diverse native forests. In a previous study, we showed that native forests support higher species richness and abundance of birds and bees than GFGP plantations and that mixed-species GFGP plantations support a higher level of bird diversity than other GFGP monocultures. Here, we use metabarcoding of arthropod diversity to test the generality of these results. Location: Sichuan, China Methods: We sampled arthropod communities using pan traps in the land-cover types concerned under the GFGP. These land-use types include croplands, native forests, and the dominant GFGP reforestation outcomes: monoculture and mixed-species plantations. We used COI-amplicon sequencing (‘metabarcoding’) of the arthropod samples to quantify and assess the arthropod community profiles associated with each land-cover type. Results: Native forests support the highest levels of arthropod species diversity, followed by mixed-species plantations, followed by bamboo and other monocultures. Also, the arthropod community in native forests shares more species with mixed-species plantations than it does with any of the monocultures. Together, these results broadly corroborate our previous conclusions on birds and bees but show a higher arthropod biodiversity value of mixed-species plantations than previously indicated by bees alone. Main conclusion: In our previous study, we recommended that GFGP should prioritize the conservation and restoration of native forests, and where plantations are to be used, we recommended promote mixed-species arrangements over monocultures. Both these recommendations should result in more effective protection of terrestrial biodiversity, which is an important objective of China’s land-sustainability spending. The results of this study strengthen these recommendations because our policy prescriptions are now also based on a dataset that includes over 500 species-resolution taxa, ranging across the Arthropoda.