Climate change is causing major changes in terrestrial ecosystems and biomes around the world. This is particularly concerning in oceanic islands, considered reservoirs of biodiversity, even more in those with a significant altitudinal gradient and high complexity in the vegetation they potentially harbour. Here, in Tenerife (Canary Islands), we have evaluated the changes in potential vegetation belts during the last 20 years by comparing them with a previous study. Considering the intimate linkage between vegetation and climate, we used a methodology based on phytosociological knowledge, ordination techniques and geostatistics, using multivariate spatial interpolations of bioclimatic data. This has allowed us to spatially detect the variations experienced by eight vegetation units during the last 20 years and incorporating a set of vulnerability metrics. New bioclimatic and vegetation cartography are provided according to the current scenario studied (1990–2019). Our results indicate that summit vegetation, humid laurel forest and thermo-sclerophyllous woodland are the habitats that have experienced a very high area loss and mismatch index, strong changes, if we consider that we are only comparing a period of 20 years. Simultaneously, the more xeric vegetation belts, the dry laurel forest and the pine forest would have benefited from this new warmer and drier climate, by gaining area and experiencing strong upward movements. These changes have not been spatially uniform, indicating that the elevational gradient studied not explain completely our results, showing the influence of the complex island topography. Effective landscape management should consider current remnants, transition capacity and movement limitations to better understand current and future vegetation responses in a global change context.

Invasive species represent a significant threat to biodiversity and ecosystem conservation, with their impacts often amplified in island ecosystems. Species distribution models (SDMs) can infer the potential habitat throughout the life of an organism and are considered a valuable tool for predicting the risk of expansion of invasive plants and animals. In our approach, we used an ensemble of four presence–absence models (GLM, GAM, Random Forest, and BART) calibrated only with data collected in Tenerife, the island with the best representation of the species, to infer the habitat suitability for Pluchea ovalis (Pers.) DC. (Asteraceae). Subsequently, we transferred the ensembled model to the rest of the Canarian Island archipelago. Our results show that under near-present conditions, the suitable areas are in the coastal and mid-elevations of the south slope sectors of Tenerife and Gran Canarian Islands, as well as a vast portion of the westernmost and drier islands, always coinciding with ravines and highly disturbed ecosystems. In addition, we forecasted the potential distribution of Pluchea ovalis under different climate change conditions (SSP126, SSP370, and SSP585), showing how its habitability would increase in the worst scenarios. Both contexts favor areas gained by the species in places where they are currently not present, revealing new suitable sectors in the westernmost islands.

Aim: Identifying climate refugia is a pressing priority for conservation planning under global change, particularly in oceanic archipelagos with high levels of endemicity and topographic complexity. Location: Canary Islands. Methods: Here, we developed a spatial framework to identify and recursively map refugia probability in the Canary Islands across a broad set of indicators, including multivariate climate analogues, topographic complexity, poleward aspect, wetness, and forestry cover. We integrated these into continuous refugia probability maps and assessed their spatial patterns across the islands. Results: Our results reveal clear east–west patterns, with highest refugia potential values concentrated in poleward‐oriented, rugged and forested areas in the western part of the archipelago. The additive integration of the different blocks enables the identification of refugia probability. The tree‐cover block highlights the role of vegetation and forest patches, promoting refugia. In drier areas, however, topography and poleward‐facing aspects become more influential, improving refugia detection on islands with strong environmental contrasts. Critically, many of the most resilient refugia remain outside existing protected areas, especially on biodiversity‐rich and heterogeneous islands, highlighting how our approach can help identify areas of high conservation potential. Main Conclusions: Our proposed framework is reproducible, data‐efficient, and transferable to other oceanic regions, providing a flexible tool for conservation decisions and adaptive design of Protected Areas systems in vulnerable landscapes. By identifying areas likely to host biodiversity under climate change, our approach supports adaptive conservation planning, protected area expansion, and climate‐informed prioritisation for managers.

Climate change poses a threat to bryophytes with restricted distributions and strong dependence on humid habitats. We assessed the climatic suitability of the moss genus Tetrastichium across the Azores, Madeira, and the Canary Islands. We compiled 90 records each for Tetrastichium fontanum and Tetrastichium virens and fitted Boosted Regression Tree models using WorldClim 2.1 bioclimatic predictors. Future suitability was projected for 2061–2080 and 2081–2100 using two global climate models under SSP3-7.0 and SSP5-8.5. Model performance was good (AUC = 0.88, sTSS = 0.81, and sensitivity ≥ 0.94). Under current and future conditions, suitable areas were unevenly distributed among archipelagos. Climatically suitable areas generally increased in the Azores but contracted substantially in Madeira and the Canary Islands. Under UKESM1-0-LL, no suitable areas in the Canary Islands remained above the climatic-suitability threshold by the end of the century. Spatial overlap between current and future predictions declined under stronger climate forcing and longer time horizons, being consistently higher for T. virens. These findings reveal the high sensitivity of Tetrastichium to climate change, identifying Madeira and the Canary Islands as areas of conservation concern. Protecting extant populations and environmentally buffered habitats will be essential for the genus’s persistence under future climates.