Although the importance of edaphic factors and habitat structure for plant growth and survival is known, both are often neglected in favor of climatic drivers when investigating the spatial patterns of plant species and diversity. Yet, especially in mountain ecosystems with complex topography, missing edaphic and habitat components may be detrimental for a sound understanding of biodiversity distribution. Here, we compare the relative importance of climate, soil and land cover variables when predicting the distributions of 2’616 vascular plant species in the European Alps, representing approximately two thirds of all European Flora. Using presence-only data, we built point-process models (PPMs) to relate species observations to different combinations of covariates. We evaluated the PPMs through block cross-validations, and assessed the independent contributions of climate, soil and land cover covariates to predict plant species distributions using an innovative predictive partitioning approach. We found climate to be the most influential driver of spatial patterns in plant species with a relative influence of ~58.5% across all species, with decreasing importance from low to high elevations. Soil (~20.1%) and land cover (~21.4%), overall, were less influential than climate, but increased in importance along the elevation gradient. Furthermore, land cover showed strong local effects in lowlands, while the contribution of soil stabilized at mid-elevations. The decreasing influence of climate with elevation is explained by increasing endemism, and the fact that climate becomes more homogeneous as habitat diversity declines at higher altitudes. In contrast, soil predictors were found to follow the opposite trend. Additionally, at low elevations, human-mediated land cover effects appear to reduce the importance of climate predictors. We conclude that soil and land cover are, like climate, principal drivers of plant species distribution in the European Alps. While disentangling their effects remains a challenge, future studies can benefit markedly by including soil and land cover effects when predicting species distributions.

- Compilation of plant species observations in the Europeans Alps from more than 200 contributors (shared upon reasonable request due to data policy)

- Summary of ~90 environmental predictors (climate, soil, land cover) via PCA axes

- Model fits/outputs/responses, predictors' evaluation/influence outputs

- Vegetation, soil and elevation type of ~4'000 plant species generated from the Flora Alpina database

- Each species' elevation values/ranges extracted with the observations and a Digital Elevation Model (DEM)

- R scripts that allowed all analysis

- Descriptive file providing links between species REF code and species name

- All the data and scripts necessary for analysis and plots are in the depository.

- All model fits and spatial predictions are on demand due to storage limitation.

- All species observations may be provided upon reasonable request due to data policy.