Land use change significantly influences landscape pattern adjustments, thereby altering ecosystem functions and service flows, ultimately impacting ecosystem service value (ESV). However, previous studies have often examined the impacts of land use change and landscape patterns on ecosystem services from a one-dimensional perspective, overlooking the complex interactions among these factors. This study proposes a “process–structure–value” response framework and applies it to a case study of the western Sichuan urban agglomeration. Its aim is to identify the spatial and temporal characteristics of land use and landscape pattern evolution. Additionally, it quantitatively evaluates the synergistic effects of these changes on ESV evolution from 2000 to 2020 using a correlation analysis. The results show that, over the past 20 years, the study area experienced a significant expansion of construction land by 184,729.41 hm², leading to the dispersion and fragmentation of arable land, grassland, and waters, resulting in an overall trend of fragmentation and diversification in landscape patterns. The ESV increased by CNY 2.619 billion, primarily due to the increased ESV associated with forest land and waters. This study found that the synergistic effects of land use processes and landscape pattern structures significantly enhanced ESV. The transition from construction land and arable land to forest land and waters notably improved the ESV. Meanwhile, increased landscape diversity and patch connectivity further enhanced the ecosystem service function. Furthermore, the ecological environment of the study area remained vulnerable despite the increased ESV. Overall, the results highlight the significant correlation between changes in land use processes, landscape patterns, and ESV, emphasizing the necessity of integrating the “process–structure–value” framework in future research to comprehensively assess the responses of land use and landscape patterns to ESV, providing a more comprehensive reference for land use planning and policy development.

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.

Climate change may alter mountain bamboo distributions and giant panda food resources. We modeled potential habitat suitability for Bashania faberi, Yushania brevipaniculata, and Chimonobambusa szechuanensis in a defined Qionglai Mountains study area in Sichuan, China, using MaxEnt, ten bootstrap replicates, and three global climate models (GCMs) for the 2050s and 2070s under SSP1-2.6 and SSP5-8.5. We tested sensitivity to predictors, thresholds, spatial grain, connectivity, and future climate products. High omission in some spatial folds and 15 records make B. faberi projections exploratory and its patch metrics indicative. At species-specific 10th-percentile (10P) thresholds, the nine-variable ensemble projected gains for B. faberi and Y. brevipaniculata only under SSP5-8.5 in the 2070s; the five-variable configuration and fixed thresholds reversed both. Each expansion was supported by one GCM, while two projected contraction. Chimonobambusa szechuanensis contracted under the nine-variable and elevation-containing configurations but increased in the temperature-inclusive diagnostic at 10P. The combined suitable-area proportion fell from 34.20% currently to 21.00–31.05% in baseline future maps; mean patch area and aggregation also declined. Averaging outcomes could produce a different change direction from averaging predictions. These projections describe conditional suitability, not food supply or functional connectivity.