Search Results (7)

Under the framework of the Rural Revitalization Strategy, optimizing the layout of rural settlements in mountainous areas and guiding their sustainable development must be based on a deep understanding of the evolution characteristics of rural settlements and suitability evaluations. This study focuses on Lixian County, located in the southwestern part of China, Sichuan Province, as the research area and employs methods such as the average nearest neighbor index, kernel density analysis, and landscape pattern index to analyze the spatiotemporal evolution characteristics of rural settlements in 2000, 2010, and 2020. Additionally, the Maxent model, based on ecological niche theory, is applied to evaluate the suitability of rural settlements. The results reveal the following: (1) Rural settlements in Lixian County exhibit a spatial distribution characterized by “sparser in the west, denser in the east, and a belt-like pattern”, with a clustered distribution trend. The number and area of settlement patches increased, with settlement distribution becoming more centralized, shapes becoming more complex, and connectivity between settlements improving. (2) The area of highly suitable land for rural settlements has decreased annually, with over 85% of the land classified as unsuitable for rural settlement layout. Suitability transitions mostly occur between adjacent levels, and it is difficult for unsuitable land to become suitable. (3) In earlier years, settlement suitability was significantly influenced by the distance to cultivated land, slope, and distance to geological hazard sites. By 2020, however, the distance to roads had become the second most important environmental factor, following the distance to cultivated land. Natural environmental factors, particularly topographic features such as elevation and slope, were found to exert a greater influence than socioeconomic factors in evaluating the suitability of rural settlements in Lixian County. These findings provide a scientific foundation for optimizing rural settlement layouts in mountainous regions, offering valuable insights into rural transformation and sustainable development not only in the upper Minjiang River area but also for reference in other similar mountainous regions. Full article

This study aims to explore the pivotal role of rural tourism in addressing the “three rural issues” and promoting rural revitalization. This study selects two representative villages in China that adopt different models of tourism development: Shibadong Village in Huayuan County, Hunan Province, which adopts a government-led model, and Yuanjia Village in Lixian County, Shaanxi Province, which follows a community-led model. This study evaluates the impact of rural tourism on rural revitalization using the Entropy-TOPSIS method. Utilizing the IPA (Importance–Performance Analysis) method and an independent samples t-test, a comparative analysis of the two models was conducted to reveal the differences in the effects of rural tourism in promoting rural revitalization between the different models. This study reveals that rural tourism positively impacts the revitalization of rural industries, ecology, culture, talent, and organization. However, the effects of tourism in promoting rural revitalization vary across different tourism development models. This study further suggests that the “multiple interlocking model” may be the future trend of rural tourism development as it can better integrate the resources of the government, communities, and enterprises to achieve more effective rural revitalization. This study deepens the theoretical link between rural tourism and rural revitalization, providing concrete guidance for practice, especially in strategies that drive comprehensive rural revitalization through tourism. Future research should further explore the corporate-led model and the multiple interlocking model and track the evolution of tourism development models through longitudinal comparisons to adapt to the changing needs of rural development. Full article

Soil fungi often operate through diverse functional guilds, and play critical roles in driving soil nutrient cycling, organic matter decomposition and the health of above-ground vegetation. However, fungal functional guilds at the early-stage restoration of disrupted subalpine forest soils remain elusive. In the present study, we collected 36 soil samples along an altitudinal gradient (2900 m a.s.l., 3102 m a.s.l., and 3194 m a.s.l.) from cut slopes (CS) (from Wenma highway) and natural soils (NS) at the Miyaluo of Lixian County, Southwest China. By applying nuclear ribosomal internal transcribed spacer (ITS) sequencing, this study revealed the ecological characteristics of fungal functional guild in the early-stage restoration of cut slope soils. The results showed that the predicted prevalence of ectomycorrhizal fungi decreased, while plant pathogens and arbuscular mycorrhizal fungi increased in CS. In the high-altitude regions (3102 m a.s.l. and 3194 m a.s.l.), the differences in communities between natural and cut slope soils were more pronounced for total soil fungi, soil saprotroph, litter saprotroph, arbuscular mycorrhizal fungi and ectomycorrhizal fungi, in contrast to the low altitude communities (2900 m a.s.l.). An opposite pattern was evident for plant pathogens. Variations in the differences of both soil properties (mainly soil pH) and community assembling processes (e.g., heterogeneous selection, dispersal limitation and drift) between natural and cut slope soils across the altitudinal gradient likely shaped the shifting patterns of community difference. This study provides valuable insights for devising restoration approaches for cut slopes in subalpine forest ecosystems, emphasizing the importance of taking soil fungal functional guilds into account in evaluating the restoration of cut slopes, and underscoring the necessity for increased attention to the restoration of soil fungi in cut slopes at the high-altitude ecosystems. Full article

To enable the accurate assessment of landslide susceptibility in the upper reaches of the Minjiang River Basin, this research intends to spatially compare landslide susceptibility maps obtained from unclassified landslides directly and the spatial superposition of different types of landslide susceptibility map, and explore interpretability using cartographic principles of the two methods of map-making. This research using the catalogs of rainfall and seismic landslides selected nine background factors those affect the occurrence of landslides through correlation analysis finally, including lithology, NDVI, elevation, slope, aspect, profile curve, curvature, land use, and distance to faults, to assess rainfall and seismic landslide susceptibility, respectively, by using a WOE-RF coupling model. Then, an evaluation of landslide susceptibility was conducted by merging rainfall and seismic landslides into a dataset that does not distinguish types of landslides; a comparison was also made between the landslide susceptibility maps obtained through the superposition of rainfall and seismic landslide susceptibility maps and unclassified landslides. Finally, confusion matrix and ROC curve were used to verify the accuracy of the model. It was found that the accuracy of the training set, testing set, and the entire data set based on the WOE-RF model for predicting rainfall landslides were 0.9248, 0.8317, and 0.9347, and the AUC area were 1, 0.949, and 0.955; the accuracy of the training set, testing set, and the entire data set for seismic landslides prediction were 0.9498, 0.9067, and 0.8329, and the AUC area were 1, 0.981, and 0.921; the accuracy of the training set, testing set, and the entire data set for unclassified landslides prediction were 0.9446, 0.9080, and 0.8352, and the AUC area were 0.9997, 0.9822, and 0.9207. Both of the confusion matrix and the ROC curve indicated that the accuracy of the coupling model is high. The southeast of the line from Mount Xuebaoding to Lixian County is a high landslide prone area, and through the maps, it was found that the extremely high susceptibility area of seismic landslides is located at a higher elevation than rainfall landslides by extracting the extremely high susceptibility zones of both. It was also found that the results of the two methods of evaluating landslide susceptibility were significantly different. As for a same background factor, the distribution of the areas occupied by the same landslide occurrence class was not the same according to the two methods, which indicates the necessity of conducting relevant research on distinguishing landslide types. Full article

Soil fungi play an integral and essential role in maintaining soil ecosystem functions. The understanding of altitude variations and their drivers of soil fungal community composition and diversity remains relatively unclear. Mountains provide an open, natural platform for studying how the soil fungal community responds to climatic variability at a short altitude distance. Using the Illumina MiSeq high-throughput sequencing technique, we examined soil fungal community composition and diversity among seven vegetation types (dry valley shrub, valley-mountain ecotone broadleaved mixed forest, subalpine broadleaved mixed forest, subalpine coniferous-broadleaved mixed forest, subalpine coniferous forest, alpine shrub meadow, alpine meadow) along a 2582 m altitude gradient in the alpine–gorge region on the eastern Qinghai–Tibetan Plateau. Ascomycota (47.72%), Basidiomycota (36.58%), and Mortierellomycota (12.14%) were the top three soil fungal dominant phyla in all samples. Soil fungal community composition differed significantly among the seven vegetation types along altitude gradients. The α-diversity of soil total fungi and symbiotic fungi had a distinct hollow pattern, while saprophytic fungi and pathogenic fungi showed no obvious pattern along altitude gradients. The β-diversity of soil total fungi, symbiotic fungi, saprophytic fungi, and pathogenic fungi was derived mainly from species turnover processes and exhibited a significant altitude distance-decay pattern. Soil properties explained 31.27−34.91% of variation in soil fungal (total and trophic modes) community composition along altitude gradients, and the effects of soil nutrients on fungal community composition varied by trophic modes. Soil pH was the main factor affecting α-diversity of soil fungi along altitude gradients. The β-diversity and turnover components of soil total fungi and saprophytic fungi were affected by soil properties and geographic distance, while those of symbiotic fungi and pathogenic fungi were affected only by soil properties. This study deepens our knowledge regarding altitude variations and their drivers of soil fungal community composition and diversity, and confirms that the effects of soil properties on soil fungal community composition and diversity vary by trophic modes along altitude gradients in the alpine–gorge region. Full article

Landslides occur frequently in Lixian County, China, and land use has changed significantly in recent decades. We obtained land use data for the years 1980, 2000, and 2018, as well as three landslide susceptibility maps from a Random Forest model. Agricultural land, low coverage grassland, water area, and urban, rural and other construction land were prone to landslides. Landslide susceptibility was low in areas of woodland, moderate and high coverage grassland, bare rock land, desert and tundra. Areas with high landslide susceptibility were mainly located in the catchment of the study region, and a 2.61% decrease in high landslide susceptibility areas over the 38-year period was primarily driven by changes in agricultural and rural land. By contrast, a 1.42% increase in low landslide susceptibility areas over the 38-year period was driven by changes in moderate and high coverage woodland and moderate coverage grassland. There is a need for effective management measures to be implemented because areas with high landslide susceptibility are still present. We also found that human aggregations, or the absence of these, vary in their effects on the areas of Lixian County most susceptible to landslides. Full article

Using advanced Differential Interferometric Synthetic Aperture Radar (InSAR) with small baseline subsets (SBAS) and Permanent Scatter Interferometry (PSI) techniques and C-band Sentinel-1A data, this research monitored the surface displacement of a large old landslide at Xuecheng town, Lixian County, Sichuan Province, China. Based on the MassMov2D model, the effect of the dynamic process and deposit thickness of the potentially unstable rock mass (deformation rate < −70 mm/year) on this landslide body were numerically simulated. Combined with terrain data and images generated by an Unmanned Aerial Vehicle (UAV), the driving factors of this old landslide were analyzed. The InSAR results show that the motion rate in the middle part of the landslide body is the largest, with a range of −55 to −80 mm/year on average, whereas those of the upper part and toe area were small, with a range of −5 to −20 mm/year. Our research suggests that there is a correlation between the LOS (line of sight) deformation rate and rainfall. In rainy seasons, particularly from May to July, the deformation rate is relatively high. In addition, the analysis suggests that SBAS can provide smoother displacement time series, even in areas with vegetation and the steepest sectors of the landslide. The simulation results show that the unstable rock mass may collapse and form a barrier dam with a maximum thickness of about 16 m at the Zagunao river in the future. This study demonstrates that combining temporal UAV measurements and InSAR techniques from Sentinel-1A SAR data allows early recognition and deformation monitoring of old landslide reactivation in complex mountainous areas. In addition, the information provided by InSAR can increase understanding of the deformation process of old landslides in this area, which would enhance urban safety and assist in disaster mitigation. Full article