Iberian relict laurissilva forests of Prunus lusitanica L. subsp. lusitanica are restricted to microclimates where orography simulates subtropical conditions. This study evaluates their habitat suitability and long-term (2076–2100) climate vulnerability using Bayesian Additive Regression Trees (BART). The occurrence dataset used to train the BART model couples original field observations with GBIF records. Unlike traditional approaches, relative humidity and fog occurrence, factors typically omitted in regional studies, are integrated into the modeling framework alongside 51 bioclimatic, edaphic, and topographic variables. The relative humidity of the wettest month, winter and summer, along with spring fog days, soil organic carbon content, soil volumetric fraction, and the bioclimatic variables BIO11 (coldest quarter mean temperature) and BIO13 (wettest month precipitation) are identified as key predictors. Results under SSP2-4.5 and SSP5-8.5 scenarios suggest potential range gains of 15-27% and low climate change vulnerability. However, the inclusion of hypothetical relative humidity and fog trends shifts the species' status to Vulnerable. Moreover, the biogeographical analysis reveals that Cantabro-Atlantic and southern populations could reach Endangered or Critically Endangered categories. It is hoped that the findings of this study will inform future restoration and conservation measures for the species, ensuring that it remains not only a relict of our past but also a witness to our future. • Iberian P. lusitanica are tertiary relicts confined to subtropical-like conditions. • A BART-SDM integrating fog and humidity, variables usually omitted, is developed. • Projected habitat gains (15-27%) are buffered when considering humidity/fog trends. • Cantabro-Atlantic and southern populations could be Endangered/Critically Endangered. • Omitting microclimates may mask climate risk for relict Mediterranean species.
Ferreiro-Lera et al. (Wed,) studied this question.