1. Due to species-specificity of the outcomes of biotic interactions, it is difficult to generalize from observed biotic interactions at the individual plant level to the effect of those interactions at the community level. To evaluate the importance of biotic interactions in shaping plant communities, it is necessary to understand how the outcomes of the complex interactions observed at the individual level can influence community structure. 2. Here, we propose a trait-based framework that identifies and organises mechanisms affecting community structure (here described with relative abundances of plant functional traits i.e. the distribution of trait values at the community level). We applied our approach to a single leaf trait, specific leaf area (SLA), to link individual responses to plant interactions with community structure (SLA distribution observed at the community level) and to test whether biotic interac- tions can predict the functional composition of subalpine grasslands. We evaluated the generality of our model through a cross-validation with a set of eight subalpine grasslands independent from the four fields used to build the model. 3. We found that competition and facilitation were able to explain the functional composition of subalpine grasslands, and the relevant fitness components (survival or growth) explaining this link changed depending on the limiting resources. When soil water availability was limiting, positive plant-plant interactions acting on survival were able to explain community structure. In contrast, when no water limitation was observed competition acting on individual growth was the main driver of community structure. 4. Our framework enables evaluation of the consequences of biotic interactions observed at individual level on community structure, thereby indicating when and where different types of plant-plant interactions are important.