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Abstract Background There is a long-term trend towards the abandonment of agro-pastoral activities in the mountain areas of Europe: the following encroachment process of semi-natural grasslands by shrubs is one of the main severe threats to the conservation of biodiversity in mountain environments. To better understand the impact of land abandonment, we analysed the reliability of plant functional groups, ant traits, and ant functional groups as indicators of land use changes. We carried out the research in Italy at four sites along a latitudinal/altitudinal gradient in three biogeographic regions (Mediterranean, Continental, Alpine). We identified three stages of a chronosequence at each site as representative of the plant succession in response to pastoral land-use abandonment. Results As expected, both the plant and ant assemblages considerably differed across sites at the species level and, within each site, among the three stages. This trend was found also using ant traits, functional groups of ants, and plant functional groups. Ant and plant communities were related in terms of composition and functionality. Harvester ants and ants with collective foraging strategy were associated with annual legumes and grasses (Therophytes); ants with a strictly individual foraging strategy with Phanerophytes. Ant traits and plant functional groups indicated significant differences among the three stages of the chronosequence. However, ant functional groups could not discriminate between the stages represented by secondary grasslands currently grazed and shrub-encroached grasslands ungrazed. Conclusion Despite some limitations of ant functional groups in explaining the succession stages of land abandonment, our results suggest that ants are a good surrogate taxon and might be used as bioindicators of land-use changes and ecosystem functioning. Furthermore, our findings indicate that the functional group approach should be applied to other European ecosystems. Finally, reducing the taxonomic complexity could contribute to developing predictive models to detect early environmental changes and biodiversity loss in mountain habitats.