The Hengduan Mountains, a global biodiversity hotspot, harbor numerous endemic plant species shaped by complex topography and microclimatic variation. However, increasing habitat fragmentation due to human activities threatens narrowly distributed species such as Cycas panzhihuaensis. To investigate its habitat suitability and inform conservation, we applied the MaxEnt model, Geodetector, and Zonation to predict potential distribution, identify key environmental drivers, and delineate priority conservation areas. Our results show that only 18.36% of the region constitutes suitable and highly fragmented habitat, primarily concentrated along the dry–hot valleys of the Jinsha and Yalong Rivers, and it is shrinking while shifting southward and southeastward under climate change. Elevation emerged as the dominant driver (q = 0.45), with strong interaction effects among topographic, climatic, soil, and anthropogenic factors, highlighting the role of environmental synergies in shaping habitat heterogeneity. Priority conservation areas covered 32% of suitable habitat and overlapped only 6.17% with existing protected areas, indicating a spatial conservation gap. These findings emphasize the need to incorporate microhabitat heterogeneity and environmental interactions in conservation planning and support the adoption of micro-reserve strategies to complement existing reserves. Our study provides a practical framework for protecting vulnerable montane species and offers insights into plant distribution dynamics in topographically complex regions.

This study assessed the conservation priorities for Cycas panzhihuaensis, a relict plant endemic to the dry-hot valleys of the Jinsha River, by integrating habitat suitability prediction with habitat quality evaluation. We used the MaxEnt model to identify its potential distribution and key environmental drivers and the InVEST model to evaluate habitat quality and degradation risk within the study area. Conservation priorities—categorized as hotspots, transition zones, and coldspots—were delineated by overlaying suitability classes with habitat quality levels. Spatial clustering of hotspots was examined using global spatial autocorrelation analysis. The results indicate that: (1) The highly suitable habitat for C. panzhihuaensis covers an area of 799.12 km², primarily concentrated in the dry-hot valleys of the Jinsha, Yalong, and Anning Rivers. January land surface temperature was the most significant environmental determinant of its distribution (contribution: 36.1%). (2) The overall habitat quality of the study region was relatively low (mean: 0.38), with a moderate risk of degradation. Areas of severe degradation spanned 14,629.31 km² (26.10% of the total area), largely coinciding with the river valleys and showing substantial overlap with the species’ suitable habitat. (3) The identified conservation hotspots (799.63 km²) exhibited a moderate and statistically significant positive spatial autocorrelation (global Moran’s I = 0.326). This integrated approach provides a spatially explicit framework for conservation planning, offering valuable insights applicable to other rare species in human-impacted landscapes.