The accurate simulation and prediction of grassland aboveground biomass (AGB) and theoretical livestock carrying capacity are key steps for maintaining ecosystem balance and sustainable grassland management. The AGB in fenced grassland is not affected by grazing and its variability is only driven by climate change, which can be regarded as the grassland potential AGB (AGB_p). In this study, we compiled the data for 345 AGB field observations in fenced grasslands and their corresponding climate data, soil data, and topographical data on the Qinghai-Tibetan Plateau (TP). We further simulated and predicted grassland AGB_p and theoretical livestock carrying capacity under the climate conditions of the past (2000-2018) and future two decades (2021-2040) based on a random forest (RF) algorithm. The results showed that simulated AGB_p matched well with observed values in the field (R² = 0.76, P < 0.001) in the past two decades. The average grassland AGB_p on the Tibetan Plateau was 102.4 g m^-2, and the inter-annual changes in AGB_p during this period showed a non-significant increasing trend. AGB_p fluctuation was positively correlated with growing season precipitation (R² = 0.57, P < 0.001), and negatively correlated with the growing season diurnal temperature range (R² = 0.51, P < 0.001). The average theoretical livestock carrying capacity was 0.94 standardized sheep units (SSU) ha^-1 on the TP, in which about 54.1% of the areas showed an increasing trend during the past two decades. Compared with the past two decades, the theoretical livestock carrying capacity showed a decreasing trend in the future, which was mainly distributed in the central and northern TP. This study suggested that targeted planning and management should be carried out to alleviate the forage-livestock contradiction in grazing systems on the Tibetan Plateau.

With the development of tourism, the number of tourists and the scope of tourism activities are increasing, and the impact of tourism on the ecological environment is gradually revealed. The ecological environment is the foundation of sustainable tourism development. Some tourist destinations lack systematic and scientific evaluation and the proper planning of tourism resources, which makes it difficult for local areas to cope with the influx of a large number of people. In these destinations, the internal system is perturbed by a series of disturbances, which leads to bad effects on the local ecological environment. In addition to endangering the development of tourism, the quality of life of local residents is also threatened. Consequently, the issues between tourism and environment have become a hot topic in the field of tourism research. Through the collection of domestic and foreign tourism literature related to ecological theories since 1990 to 2020, the status of the application of various ecological theories in the field of tourism is revealed, such as life cycle theory, landscape ecology theory, carrying capacity theory, biodiversity, ecological niche theory and ecological footprint theory. This analysis found that the application of these theories to tourism mainly focuses on empirical research, and there are few studies on the basic theories related to it. In the empirical research, innovation of the research methods is basically absent. Therefore, future research should pay more attention to the theoretical research of ecological theory in the field of tourism, and combine modern science and technology in the practical application to strengthen the innovation of research methods. In addition, the prospect of applying ecological theories in future tourism research is discussed.

Green development is an important way to achieve global sustainable development goals, and has become one of the main research hotspots in recent years. Balancing economic development and environmental protection has turned out to be a great challenge in Beijing, the capital of China, which can provide some suggestions on ecological civilization construction and green development for other cities. However, there have been limited studies on this crucial topic. Therefore, based on the statistical data for Beijing from 2006 to 2016, this paper constructed the green development evaluation system of Beijing, and used the Projection Pursuit Model and spatial analysis method to analyze the spatial and temporal changes in its green development level. We also aimed to further explore the influences of key factors on green development. Our results illustrated that: (1) the overall and average levels of green development in Beijing showed significant increasing trends; (2) there are obvious spatial differences in green development among districts in Beijing, with the outer districts showing higher values; and (3) the environmental condition and human consumption were two important factors driving the green development in Beijing.