Introduction: Global warming is reshaping species distribution patterns. Methods: Based on climatic, topographic and soil data, the Coffea arabica planting regions with different levels of ecological suitability in different periods and the environmental factors that have the largest impact on ecological suitability were simulated using the Biomod2 model to clarify the influence of climate change on the suitable habitats of C. arabica in China. Results: The results revealed that the temperature seasonality (Bio4), mean temperature of the coldest quarter (Bio11), precipitation of the warmest quarter (Bio18) and elevation (Elev) were the main environmental factors affecting the distribution of C. arabica . Under current climatic conditions, the suitable habitats of C. arabica are primarily distributed across Yunnan, Hainan and Guangxi Provinces, with southwestern Yunnan identified as a core highly suitable area. Under future climates, the total area of suitable habitats for C. arabica will generally expand, with habitat size positively correlated with temperature stress intensity. Specifically, under the SSP5-8.5 scenario, the suitable habitat area will reach 184.29 × 10 ⁴ km ² , tripling the current extent, and may expand toward higher latitudes. Discussion: Climate warming had increased the area of suitable regions for C. arabica in China, which provides a theoretical basis for the introduction, cultivation of C. arabica , as well as the planning and management of plateau characteristic agricultural production.

Introduction: Drought is a major abiotic stress limiting coffee production globally. While grafting improves abiotic stress tolerance, the relative contributions of scion and root stock to drought resistance in intraspecific and interspecific grafted Coffea seedlings remain unclear across different stress intensities. Methods: We hypothesized that scion genotype dominates drought responses under severe water stress, whereas rootstock effects prevail under normal irrigation. To test this, we conducted a 120-day pot experiment using daily weighing and replenishment, with three treatments: normal supply (18-25% soil water), mild drought (15-17%), and severe drought (10-12%). Two C. canephora scions (‘Dafeng No.1’,‘Reyan No.5’) were grafted onto intraspecific (‘Reyan No.2’) and interspecific (‘Charlie No.16’) rootstocks. Results: ‘Reyan No.5’ scion conferred superior drought tolerance under severe stress via stronger membrane stability (lower malondialdehyde, MDA), higher osmotic adjustment, and more stable antioxidant defense (super oxide dismutase, SOD; peroxidase, POD; catalase, CAT) .‘Dafeng No.1’ showed higher water use efficiency (WUE) under mild stress but suffered greater oxidative damage. Principal component analysis confirmed scion genotype explained 44. 78% of total physiological variation. Discussion: These findings clarify scion dominance in severe drought tolerance and guide drought-resistant coffee grafting selection.

This study investigated the differences in rhizosphere soil properties and their associations with microbial communities across eight Coffea arabica cultivars cultivated under uniform conditions at the Kangping Education and Research Base in Pu’er, Yunnan. We assessed arbuscular mycorrhizal fungi (AMF) colonization and spore density, analyzed soil chemical properties—including pH, organic matter (OM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and slowly available potassium (SK)—and characterized microbial communities via high-throughput sequencing. The findings of this study demonstrate that coffee variety significantly influences the contents of available nutrients (AN, AP, AK) and OM in the rhizosphere soil. Sequencing indicated that Ascomycota dominated the fungal community, Chloroflexi and Proteobacteria were the primary bacterial phyla, and Glomus and Sclerocystis were the predominant AMF genera. Analysis of alpha diversity showed that in the bacterial community, S8 exhibited the highest diversity and richness, while S6 showed the lowest. For the fungal community, S6 had the highest diversity, S2 displayed the highest richness, and S5 showed the lowest values for both diversity and richness. Within the AMF community, S8 demonstrated the highest diversity, S7 exhibited the highest richness, and S6 had the lowest diversity and richness values. Overall, bacterial diversity surpassed fungal diversity. Redundancy analysis identified AK as a common key factor influencing both bacterial and fungal communities. Besides AK, OM and TN were also significant drivers for the fungal and bacterial communities, respectively, while the AMF community was most strongly associated with SK