Based on land-use change data, this paper constructed an ecological resilience evaluation model from the three dimensions of resistance, adaptability, and regeneration capacity. The spatial and temporal evolution characteristics of the ecological resilience of urban agglomeration on the northern slope of Tianshan Mountain (UANST) from 1990 to 2020 were studied. The key factors affecting the spatial distribution of ecological resilience were detected. The results showed that (1) from 1990 to 2020, the mean ecological resilience values of the UANST were 0.3371, 0.3326, 0.3330, and 0.3240, showing an overall decreasing trend. The regions with low and medium values of ecological resilience contributed the most to these values. (2) The spatial distribution of the ecological resilience of the UANST was uneven, showing a “sandwich”-type distribution with low values in the south and north of the study area and high values in the middle of the study area. During the study period, the ecological resilience in the north part of the study area declined overall, while the ecological resilience in the south part of the study area increased continuously. (3) The results of the Geodetector model showed that natural and human factors jointly influenced the spatial distribution of the ecological resilience of the UANST, with natural factors dominating and temperature changes being the most sensitive. Finally, the impact of intense human activities on the ecological resilience of the UANST is increasing.

Globally, mountains have suffered enormous biodiversity loss and habitat degradation due to climate change and human activities. As an agent of biodiversity, evaluating habitat quality (HQ) change is an indispensable key step for regional ecological security and human well-being enhancement, especially for fragile mountain ecosystems in arid areas. In this study, we aimed to propose an integrated framework coupled with the Normalized Difference Vegetation Index (NDVI) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST)-HQ module to improve the effectiveness and accuracy of HQ estimation. We highlighted the Tianshan Mountains in Xinjiang as an example to validate the model, as it is a typical representative of mountain ecosystems in the temperate arid zone. Specifically, we aimed to assess the spatiotemporal dynamics of HQ over the past two decades and investigate its influencing factors using a geographical detector model. The results show that, first, grassland and unused land were the main land-use types in the study area. The land-use transitions were mainly concentrated in grassland, woodland, water body, and unused land. Second, the total area of very important habitats and general habitats accounted for over 70% of the Tianshan Mountains. The average HQ decreased from 0.5044 to 0.4802 during 1995–2015. Third, the HQ exhibited significant spatial differentiation, and the Ili River Valley and Kaidu River Basin were the hot spots, while the south and east of the Tianshan Mountains were the cold spots. Habitat quality was strongly related to the terrain gradient, with an inverted “U” type. Protected areas of different categories played a vital role in biodiversity conservation. Finally, soil type, land-use change, precipitation, temperature, and grazing intensity were the dominant factors in response to HQ change for both the total Tianshan Mountains and sub-regions, followed by elevation, the relief degree of the land surface, gross domestic product, population density, and distance to tourism attractions. The interaction effects of the influencing factors were improved compared to the effects of the individual factors in each zone. Furthermore, these results provide decision-making criteria for formulating a scientific and systematic protection of ecology and restoration planning systems to enhance the capacity to address climate change.

Geodiversity is considered a new tool to exploit the resources of regional and local geotourism. Hitherto, few assessments of geodiversity have been conceived for huge geographic units. The spatial pattern of geodiversity in the Tibetan Plateau (TP) is the purpose of this study. A total of 96 abiotic units in six geo-groups of hydrology, pedology, landform, elevation, geology, and geosites were quantified and normalized to assess the geodiversity index. Geosites that represent interdisciplinary and specific abiotic elements are included as an independent component in the parameters of geodiversity assessment. The TP was divided into 1145 areas by fishnet, for counting of abiotic units, geodiversity calculation, and visualization of findings. The results indicated that the Pamir Plateau, Mt. Kunlun, the Delingha area, Mt. Qilian, the Xining area, Langmusi Town, Mt. Siguniang, Mt. Hengduan, the Nyainqentanglha Range, and the Lhasa area are the zones with very high geodiversity. The low geodiversity areas are mainly concentrated in the Qaidam Basin, the Qingnan Plateau, and the South Tibet region. In the TP, international tourist destinations such as UNESCO World Natural Heritage Sites and Global Geoparks, are developed in areas of high geodiversity. The spatial pattern of geodiversity could be indicative of geotourism potential, and be used to guide the development planning of geotourism in the TP. The quantitative assessment of geodiversity also provides a new parameter for geoconservation in China.