Environmental heterogeneity and plant-plant interactions are key factors shaping plant communities. However, the spatial dimension of plant-plant interactions has seldom been addressed in field studies. This is at least partially rooted in a lack of methods that can accurately resolve functional processes in a spatially explicit manner. Isoscapes, that is, spatially explicit representations of stable isotope data, provide a versatile means to trace functional changes on spatial scales, for example, related to N-cycling (foliar δ15N) and water use efficiency (WUEi, foliar δ13C). In a case study in a nutrient-depleted Mediterranean dune ecosystem, we analysed the spatial impact of the invasive N2-fixing Acacia longifolia on three native species of different functional types using δ15N and δ13C isoscapes and spatial autocorrelation analyses. Isoscapes revealed strong spatial patterns in δ15N and δ13C with pronounced species-specific differences, demonstrating distinct spatial ranges of plant-plant interactions. A coniferous tree and an ericaceous dwarf shrub showed significant enrichment in δ15N within a range of 5-8 m surrounding the canopy of A. longifolia, indicating input of N originating from symbiotic N2-fixation by the invader. In the dwarf shrub, which was most responsive to invader influence, enrichment in δ13C additionally demonstrated spatially explicit changes to WUEi, while a native N2-fixer was unresponsive to the presence of the invader. Furthermore, δ15N and δ13C isoscapes yielded different patterns, indicating that plant-plant interactions can have distinct spatial distributions and ranges based on the process measured. Additionally, the magnitude of the effect differed between field situations with high and low invasion pressure. This study highlights that the spatial scale must be accounted for when assessing the effects and outcome of species interactions. Functional tracers such as stable isotopes enable us to quantify spatial ranges of plant-plant interactions, providing empirical data that can help to better understand and predict complex species interactions in multifaceted natural environments.