The application of resilience thinking to tourism destination research is a new perspective on sustainable tourism and has gradually become a popular research topic. Some literature has been conducted on tourism destination resilience, but there has not been a comprehensive review and analysis of the whole field. This study was based on the literature from 2000 to 2021 in the Web of Science core collection database. The collaboration analysis, literature co-citation analysis, keyword co-occurrence, burst detection analysis in CiteSpace, and qualitative analysis were adopted to conduct a holistic tourism destination resilience research review. The results indicated that the United States, Australia, China, and the United Kingdom were the primary countries involved in tourism destination resilience research. Five hot research themes were obtained. (1) concept and connotation of tourism destination resilience, (2) drivers of tourism destination resilience, (3) sustainable management framework and practices, (4) perception of tourism destination resilience, and (5) the resilience of the tourism community. Furthermore, four research gaps and future directions were proposed in this study, including the theoretical framework of tourism destination resilience, assessment of tourism destination resilience, sustainable management and resilience, and application of advanced technology in tourism destination resilience. This study assists researchers in understanding the development and future research directions in tourism destination resilience research.

Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.

The evaluation of ecological risk and the construction of ecological security patterns are significant for the conservation of World Natural Heritage sites with high outstanding universal value. This paper constructed a landscape ecological risk evaluation framework for Bayinbuluke using the three aspects of the “nature–society–landscape pattern” and a cumulative resistance surface from the risk evaluation results. The ecological sources were identified based on Morphological Spatial Pattern Analysis (MSPA) and the landscape index. Finally, the Minimum Cumulative Resistance model (MCR) and gravity model were used to obtain both key ecological corridors and general ecological corridors. The results showed that: (1) the influencing factors of landscape ecological risk were, in order of strongest to weakest, landscape pattern factors, natural factors, and social factors; (2) the spatial differences in terms of landscape ecological risk within the study area could be identified. Low-risk areas were mainly concentrated in the core area, high-risk areas were mainly in the outer buffer zone, and the overall ecological risk level at Bayinbuluke was high; and (3) a total of four key corridors and ten general corridors could be constructed. This study provides a reference for decision-making on the ecological security and protection of heritage sites.

Tourism is one of the core industries driving the economy on the Tibetan Plateau towards green development. Adopting the improved gravity model, social network analysis, and quadratic assignment procedure, this paper explores the structure and evolution characteristics of the tourism economic network on the Tibetan Plateau from 2015 to 2019. The results are as follows: (1) the tourism economic strength increased over time, but it was generally higher in Qinghai Province and lower in Tibet. (2) The network density exhibited an upwards trend overall. (3) The structure of the tourism economic network presented a significant core–periphery distribution pattern. Xining, Haixi, and Lhasa acted as a bridge between the spatial network structure of the tourism economy and had a structural hole advantage. However, some remote cities, such as Ali, Naqu, and Guoluo, had low network centricity. (4) The quadratic assignment procedure regression analysis showed that the A-level attractions and star-rated hotels significantly advanced the formation of the spatial association. This study concludes with recommendations for promoting tourism economic associations for policy-makers.

The pro-environmental behaviour intentions (PEBIs) of tourists is a popular topic in tourism geography research. Visitors are important stakeholders in the development and conservation of World Natural Heritage sites (WNHs). Based on the perspective of the Mehrabian–Russell (M-R) theory, to advance our understanding of the transmission mechanism and mediation effect of the “perception–emotion–behaviour” chain of visitors at World Natural Heritage sites, we introduced two variables, namely heritage genes perception (HGP) and environmental knowledge perception (EKP), combined with place attachment (PA) and pro-environmental behaviour intentions (PEBIs), and scientifically constructed the conceptual model of the “EHPP model”, consisting of EKP, HGP, PA and PEBIs. Taking the Bayanbulak Heritage Site as an example, the EHPP model was fitted and tested using the structural equation model (SEM). The results show that: (1) the EHPP model is applied to fit the “cognitive–emotional–behaviour intentions” chain of visitors in WNHs and passed the empirical test; (2) there were positive and significant effects of EKP on HGP, and EKP indirectly affects PEBIs via HGP and PA; (3) place dependence (PD) had a significant and positive influence on place identity (PI); and (4) compliance with pro-environmental behaviour intentions (CPEBIs) had a direct positive influence on pro-environmental behaviour intentions (PPEBIs). The findings of this study provide empirical references for stimulating the pro-environmental behaviour intentions of tourists at World Natural Heritage sites.

The conservation of World Natural Heritage Sites has become a global concern. The identification of priority conservation areas can preserve the value of heritage sites while promoting sustainable development, which is important for balancing the conservation and development of heritage sites. This paper proposes an integrated framework for the identification of priority conservation areas for natural heritage sites based on landscape ecological risks (LERs) and ecosystem services (ESs), taking the Bogda heritage site in Xinjiang, China as a case study. The innovative approach combined the natural and cultural elements of natural heritage sites and included the following steps: (1) the LER index, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and questionnaire method were adopted to assess the LERs and ESs of Bogda heritage sites during 1990–2018; (2) ordered weighted averaging (OWA) was used to identify conservation priorities by weighing LERs and ESs; and (3) the optimal priority conservation area was determined by comparing the conservation efficiencies under different scenarios. The results revealed that the LER, carbon storage (CS), habitat quality (HQ), aesthetic value (AV), and recreational value (RV) showed significant spatiotemporal variation. The most suitable priority conservation area was located at the central forestlands and high-coverage grasslands, with conservation efficiencies of 1.16, 2.91, 1.96, 1.03, and 1.21 for LER, CS, HQ, AV, and RV, respectively. Our study demonstrated that integrating LERs and ESs is a comprehensive and effective approach to identifying conservation priorities for heritage sites. The results can provide decision support for the conservation of the Bogda heritage site and a methodological reference for identifying conservation priorities for natural heritage sites. Furthermore, this study is also an effective application of LERs and ESs in identifying priority conservation areas.