The stability of ecosystems in high mountain canyon areas is poor, and the interaction between humans and the land is complex, making these ecosystems more vulnerable to destruction. Quantitatively assessing the ecosystem service value (ESV) in high mountain canyon areas and revealing its spatiotemporal evolution patterns and driving factors play a crucial role in the construction of regional ecological barriers and the assurance of ecological security. This study focuses on the Upper Minjiang River as the research area, using the InVEST model and the Equivalent Factor Method to estimate ESV. This combination aims to address the inadequacy of the Equivalent Factor Method in reflecting the variability of ESV across different regions, and the sensitivity of the InVEST model to data changes that results in insufficient accuracy of ESV assessments. By harnessing spatial au-tocorrelation and the geodetector method, we unravel the spatiotemporal evolution characteristics and driving factors of ESV. The results show that: (1) From 2000 to 2020, the ESVs estimated by the two estimations increased by 31.28% and 22.47%, respectively, both indicating that the eco-environment quality of the upper Minjiang River has been continuously improved. (2) When Moran’s I was greater than 0.5 (p < 0.05), the spatial clustering of “High-High” and “Low-Low” ESV was obvious. It is clear that the ESV varies geographically. High values are primarily found in the study area’s center and southern regions, as well as on both banks of the Minjiang River, whereas low values are more common in the region’s northern region. (3) Slope and human activity intensity (HAI) are the principal contributors to the spatial differentiation of the ESV, more than 60% of the interaction types between the two factors were classified as dual-factor enhancement. The synergistic reinforcing effects of HAI, slope, elevation, and temperature collectively shape the shifts in ESV spatial distribution. This study offers a novel evaluative lens on the ESV of the Upper Minjiang River area, supplying a sturdy data support for crafting specific ecological preservation and rejuvenation strategies in the coming years.

Human activities are constantly affecting ecological space, and the construction of ecological security patterns to ensure ecological security has become an issue that must be considered for sustainable development. At present, little attention has been paid to the ecological security of cities with a high number of nature reserves. In this study, we took Garze Tibetan Autonomous Prefecture in China, which has many nature reserves, as the research object to construct an ecological security pattern with nature reserves as ecological sources. Firstly, Fragstats 4.2 and ArcGIS 10.4 were used to obtain the ecological risk evaluation results of the study area landscape. Secondly, a “nature–society–landscape” resistance factor system and an ecological resistance surface were constructed using a minimum resistance model. Finally, the ecological safety zone of the nature reserve was divided, and the ecological safety pattern of the nature reserve was established. (1) The ecological risk of the study area shows a spatial distribution pattern of “low in the northwest and high in the southeast”, with low and moderate-low ecological risk dominating; (2) The study area has formed an ecological security pattern consisting of 9 ecological sources, 35 ecological nodes, 8 ecological corridors with a total length of 702.96 km and 4 ecological safety zones; (3) The ecological security pattern of nature reserves in the study area was divided into four categories: low, medium, high and moderate-high ecological safety zones, accounting for 20.62%, 27.34%, 24.48% and 27.55%, respectively. This study provides a new framework for the construction of urban ecological safety patterns and offers scientific guidance for the conservation and management of nature reserves and urban ecology.

The scattered, isolated, and closed nature of rural settlements in northwest Sichuan is a constraint on the high-quality development of rural areas. Determining the spatial differences and driving forces of rural settlements in this area is the essential prerequisite for promoting rural revitalization. In this paper, the methods of the nearest neighbor index, the Voronoi diagram, and the Geodetector are used to analyze the spatial distribution characteristics of rural settlements and explore the driving factors of their spatial differences. The key findings are as follows. (1) The rural settlements exhibit the feature of “an extensive dispersion with localized concentrations”. The spatial distribution is in the shape of dots, strips, and branches along the river valley. (2) The number and land use scale of rural settlements decreases from east to west. The spatial differences in settlement morphology have a clear feature that the settlement morphology along the river and road is more complex, while the settlement morphology in the plateau area and the river valley is relatively regular. (3) Mountain disasters and arable land resources have the greatest impact on the spatial differences of the settlements. The location and form of the settlements are greatly affected by the altitude and accumulated temperature, and the settlement scale is significantly affected by the traffic conditions and the scenic spots. The mutually reinforcing role of the driving factors is remarkable, especially the reinforcing effects of the enhancement between the arable land resources and other factors. The research results provide data support for the reconstruction, improvement, and high-quality development of rural settlements in this region.

Ecosystem service value (ESV) is a key indicator for evaluating ecosystem services. Thus, a unique quantitative assessment instrument that comprehensively and objectively evaluates ESV is of great significance for protecting regional ecosystems and achieving sustainable development. Based on data for meteorology, hydrology, soil use, and land use, this paper comprehensively employs the InVEST model, spatial autocorrelation, and geographic detectors to study the spatiotemporal characteristics and driving forces of spatial variations in ESV in the upper reaches of the Minjiang River. The results indicate the following: (1) The ecosystem service capacity of the study area has continuously improved, with the ecosystem service value (ESV) increasing by USD 4.078 billion over 20 years. Soil conservation has made the most significant contribution to the growth of ESV, accounting for over 85%. (2) The distribution of ESV exhibits a “lower in the northwest, higher in the southeast” trend. The Moran’s I value for each year exceeds 0.7, indicating characteristics of High–High and Low–Low aggregation. (3) Slope plays a dominant role in causing the spatial differentiation of ESV, contributing 30.9%. Slope is followed by HAI at 19.7% and the urbanization rate at 16.8%. Rainfall has the least impact at 4%. (4) The results from the multi-factorial interactions reveal that all factors experience synergistic enhancement effects when interacting. The spatiotemporal differentiation of ESV is the result of multiple factors acting in conjunction, underscoring the importance of coordinated efforts in ecological restoration and comprehensive environmental management in the upper reaches of the Minjiang River. The methodology of this research could be applied to assess the impact of natural changes and human activities on ESV. The findings offer theoretical support for regional resource and environmental management, as well as ecological compensation decision making.