Ensemble modeling uncovers climate change-driven distribution shifts of Fargesia nitida (Mitford) P. C. Keng ex T. P. Yi, a primary food source for giant panda

<i>Fargesia nitida</i> (Mitford) P. C. Keng ex T. P. Yi is an alpine bamboo species endemic to the Hengduan Mountains (HDM). As the primary food source for giant pandas and a key component of subalpine ecosystems, it plays an irreplaceable ecological role. However, its exceptionally long flowering cycle (up to 109 years) and limited dispersal ability render it highly vulnerable to climate change impacts, while the potential shifts in its distribution under future climate scenarios remain inadequately explored. In this study, we employed ensemble modeling (Biomod2) to project the suitable habitats under current and future climate scenarios (SSP126, SSP245, SSP585) for the 2050s and 2090s, based on 78 occurrence records and seven environmental variables. Results showed that the ensemble model exhibits superior predictive performance (AUC = 0.995, TSS = 0.957, Kappa = 0.753) compared to optimized MaxEnt and other individual models. Temperature seasonality (bio4) and minimum temperature of the coldest month (bio6) were identified as the most influential factors. Currently, the total suitable habitat area is estimated at 83.10 × 10⁴ km², with a central distribution located primarily in the HDM region and its adjacent areas. Although future projections suggest an overall expansion of the total suitable area, the highly suitable habitats-corresponding to the species' current occurrence area-show a persistent contraction. By the 2090s, this contraction will exceed 56% under the SSP585 scenario. Distribution centroid analyses revealed that the current center of <i>F. nitida</i> is located in northern Sichuan. It will shift northward to higher latitudes under the low emission scenario, but southwestward to higher altitudes under the high emission scenario. These findings underscore the vulnerability of <i>F. nitida</i> to climate change and provide critical scientific insights for the development of targeted conservation strategies, as well as for the effective management of giant panda habitats and subalpine ecosystems under future climatic conditions.