The R package biomod2 is one of the most widely used and versatile tools for species distribution modelling (SDM), enabling ecologists to calibrate, evaluate, and project species–environment relationships across space and time using multiple modelling algorithms and ensemble forecasting. Since its initial release, the package has undergone continuous improvement. Here, we present its latest and most comprehensive version, which substantially expands its scope by integrating diverse ecological data types into a unified modelling workflow. Beyond presence-only and presence–absence data, biomod2 now accommodates a wide range of abundance formats, including counts, multi-class abundance categories, and relative or absolute abundances, thereby also extending its applications to modelling biomass, land cover, and habitat suitability. We have fully restructured the workflow to improve usability and reproducibility, introducing clearer function organization, standardized parameter names, and substantially revised documentation. The update also includes new methodological features such as enhanced cross-validation schemes, improved pseudo-absence selection strategies, expanded model parametrization options, additional algorithms, and new tools for exploring and visualizing outputs. Together, these developments provide a more flexible, transparent, and easily shareable framework for species distribution modelling, supporting robust inference across a broad range of ecological questions.

Climate change and land-use changes are key drivers of global biodiversity loss. Many species are shifting to higher elevations or latitudes in response to global warming, often encountering unfavorable land-use conditions during the shift. This leads to reduced range size and increased extinction risks, particularly for mountain species, often confined to narrow, high-altitude habitats. Predicting future distributions of mountain species requires an accounting for their bioclimatic responses, detailed topographical distribution, land-use preferences, and ability to colonise new areas via dispersal mechanisms. These elements are rarely considered together over large scales. Here, we projected the future distribution of 32 mountain mammal and 344 non-migratory mountain bird species by 2050 under different emission scenarios (SSP-RCP 1-2.6 and SSP-RCP 5-8.5). Using Species Distribution Models (SDMs) that incorporated topography, climate, and land-use data, we assessed the impacts of global change on species’ ranges across mountain regions worldwide, accounting for realistic dispersal scenarios. Under the high-emissions scenario, species were projected to experience significantly greater range loss compared to the low-emissions scenario, with a difference of 17% of loss for birds and 16% for mammals. The number of species that shift their range also increased, passing from 73 to to 84. The most severe range losses were projected for species located in tropical mountain ranges, while European and North American mountains showed lower losses, highlighting substantial regional differences in vulnerability. When land-use changes were included in the models, projected range losses increased further, particularly under the low-emissions scenario (+2%). Our findings emphasize the importance of considering both climate and land-use changes when assessing biodiversity risks in mountain regions. Our results highlight the urgency of mitigating climate change and managing land use to preserve the unique biodiversity of these areas.