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There is a World Heritage Craze in China. China claims to have the longest continuous civilization in the world and is seeking recognition from UNESCO. This book explores three dimensions of the UNESCO World Heritage initiative with particular relevance for China: the universal agenda, the national practices, and the local responses. With a sociological lens, this book offers comprehensive insights into World Heritage, as well as China’s deep social, cultural, and political structures.

China's plans to expand exponentially its exploitation of Tibet's natural resources will have terrifying consequences for land and people. This book is an entirely unique, authoritative guide through the torrent of online posts, official propaganda and exile speculation.

The unified right confirmation and registration of natural resources in sea areas (URCRNRSA) has been considered a key approach to the effective management and sustainable utilization of marine resources. In China, the system of URCRNRSA is insufficient due to the lack of central auditing supervision and public participation. In this study, the mechanism of stakeholder interaction is clarified based on the game relationship among the tripartite of the central government, local governments, and the public. The evolutionary process of tripartite decision-making is simulated with an evolutionary game model. On this basis, the strategic choices of the tripartite were analyzed in the four evolutionary scenarios of high-quality URCRNRSA. It was demonstrated that the tripartite could jointly affect the URCRNRSA through cooperation-constraint, principal-agent, and incentive-compatibility relationships. The most effective, realistic, and feasible URCRNRSA strategy was the trinity system with local government high-quality rights confirming, the central government auditing as a hard constraint and the public participating as a soft constraint. The main influencing factors for the tripartite to make different strategy selections were clarified through parameter sensitivity analysis, including cost, benefit, reward, and punishment. Accordingly, the policy recommendations were put forward to ensure the stable and efficient implementation of the URCRNRSA in China.

This is the first environmental history of China during the three thousand years for which there are written records. It is also a treasure trove of literary, political, aesthetic, scientific, and religious sources, which allow the reader direct access to the views and feelings of the Chinese people toward their environment and their landscape.Elvin chronicles the spread of the Chinese style of farming that eliminated the habitat of the elephants that populated the country alongside much of its original wildlife; the destruction of most of the forests; the impact of war on the environmental transformation of the landscape; and the re-engineering of the countryside through water-control systems, some of gigantic size. He documents the histories of three contrasting localities within China to show how ecological dynamics defined the lives of the inhabitants. And he shows that China in the eighteenth century, on the eve of the modern era, was probably more environmentally degraded than northwestern Europe around this time.Indispensable for its new perspective on long-term Chinese history and its explanation of the roots of China's present-day environmental crisis, this book opens a door into the Chinese past.

We used the line transect method and infrared camera traps to research the sable and yellow-throated marten in Taipinggou National Nature Reserve, Heilongjiang, China, to understand the distribution and overlap of their habitats and niches. In our study, the results showed that the habitat suitable for sables was larger than that for yellow-throated martens and that there is a partial overlap in terms of the suitable habitat for both species. There was a high degree of niche overlap between the sable and yellow-throated marten, primarily influenced by four environmental variables, i.e., “Distance from Settlements”, “Distance from Roads”, “Slope”, and “Distance from Coniferous and Broadleaved Mixed Forest”. This study can offer valuable insights for the development of policies aimed at conserving and managing sables and yellow-throated martens. The global focus on fostering harmonious interactions and promoting rational coexistence among wildlife species to uphold or reinstate biodiversity remains a prominent area of interest. We conducted a study on the sable and yellow-throated marten in Taipinggou National Nature Reserve, Heilongjiang, China, using the line transect method and infrared camera traps from 2022 to 2023. We then analyzed the overlap of their suitable habitats and niches with the aim of gaining insight into the interspecific competition between these two species. We found that the suitable habitat areas for the sable and yellow-throated marten were 55.20 km[sup.2] and 23.28 km[sup.2], accounting for 24.86% and 10.48% of the total area of this study, respectively. The overlap between the suitable habitats for the sable and yellow-throated marten was 15.73 km[sup.2], accounting for 28.5% and 67.6% of their suitable habitat, supporting our Hypothesis 1. The first principal component (Dim1) of the niche explained 35.4% of the overall variability, which is mainly related to the environmental variables “Distance from Settlements” and “Distance from Roads”. Overall, 25.5% of the total variability was explained by the second principal component (Dim2), associated with “Slope” and “Distance from Coniferous and Broadleaved Mixed Forest”. The niches occupied by the sable and yellow-throated marten were both off-center of the environmental background space, with the niches of the sable being larger than those of the yellow-throated marten. Schoener’s D index was 0.56, indicating a high degree of niche overlap between the sable and yellow-throated marten, supporting our Hypothesis 2. Our study is helpful in terms of formulating conservation and management policies for the sable and yellow-throated marten.

Abstract From June 10 to 13, 2019, continuous heavy rainfall occurred in Longchuan County, Guangdong Province, yielding a cumulative rainfall of nearly 270 mm. The heavy rainfall triggered a large number of landslide disasters and formed three hardest-hit areas. In this paper, Mibei village, Beiling town, Longchuan County, is chosen as the research object; detailed field investigation data, satellite remote sensing images, rainfall monitoring data, and artificial rainfall physical model test results are integrated; the temporal and spatial distribution characteristics of rainfall-induced group-occurring landslides in the study area are obtained; and the rainfall instability mechanism of granite residual soil slopes is explained. Under the influence of continuous heavy rainfall from June 10 to 13, 2019, 327 landslides developed in Mibei village, Beiling town, and these landslides were mainly distributed in low mountainous areas, of which the sections at elevations from 300 ~ 400 m and slopes ranging from 35 ~ 45° were the most susceptible to landslide disasters. Continuous rainfall on June 10 and 11 was the controlling factor leading to these large number of landslides, with numerous landslides occurring from 20:00 on June 11 to 04:00 on June 13. These group-occurring landslides exhibited the characteristics of a considerable rainfall lag. The deformation and failure characteristics of the numerous observed landslides within the study area were highly similar, mainly involving traction sliding failure, and the sliding mass thickness ranged mostly from 1.5 ~ 3 m. The flow pattern characteristics of unconsolidated deposits after landslide instability were significant. According to the deformation and failure characteristics of landslides and the rainfall infiltration pattern, the development of landslides was divided into stages in this paper. Due to the difference between the rainfall intensity and permeability of granite residual soil, the main influence depth of heavy rainfall was limited to the superficial zone of slopes, which is the main reason why the shallow surface zone was damaged by landslides. Under the action of continuous heavy rainfall, a saturated seepage field was established in the shallow surface zone of slopes. Driven by gravitational potential energy, this led to an uneven distribution of the slope saturation zone. Attenuation of the mechanical strength of saturated soil reduced the slope stability, and sliding failure consequently occurred in the shallow surface saturation zone. In regard to excavated slopes, anti-sliding force reduction and free face formation enhanced the slope’s susceptibility to sliding failure under the influence of heavy rainfall, which is also the reason for the large-scale distribution of landslides along the X158 county road.

Landslides are a common natural hazard that causes casualties and unprecedented economic losses every year, especially in vulnerable developing countries. Considering the high cost of in-situ monitoring equipment and the sparse coverage of monitoring points, the Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique were used to conduct landslide monitoring and analysis. The Muyubao landslide in the Three Gorges Reservoir area in China was taken as a case study. A total of 37 images from March 2016 to September 2017 were collected, and the displacement time series were extracted using the Stanford Method for Persistent Scatterer (StaMPS) small baselines subset method. The comparison to global positioning system monitoring results indicated that the InSAR processing of the Muyubao landslide was accurate and reliable. Combined with the field investigation, the deformation evolution and its response to triggering factors were analyzed. During this monitoring period, the creeping process of the Muyubao landslide showed obvious spatiotemporal deformation differences. The changes in the reservoir water level were the trigger of the Muyubao landslide, and its deformation mainly occurred during the fluctuation period and high-water level period of the reservoir.

There are significant differences in the dominant driving factors of rocky desertification evolution in different historical periods in southwest karst mountainous areas. However, previous studies were mostly conducted in specific periods. In this study, taking Bijie City as an example, the spatial and temporal evolution pattern of rocky desertification in Bijie City in the recent 35 years was analyzed by introducing the feature space model and the gravity center model, and then the dominant driving factors of rocky desertification in the study area in different historical periods were clarified based on GeoDetector. The results were as follows: (1) The point-to-point B (bare land index)-DI (dryness index) feature space model has high applicability for rocky desertification monitoring, and its inversion accuracy was 91.3%. (2) During the past 35 years, the rocky desertification in Bijie belonged to the moderate rocky desertification on the whole, and zones of intensive and severe rocky desertification were mainly distributed in the Weining Yi, Hui, and Miao Autonomous Region. (3) During 1985–2020, the rocky desertification in Bijie City showed an overall weakening trend (‘weakening–aggravating–weakening’). (4) From 1985 to 2020, the gravity center of rocky desertification in Bijie City moved westward, indicating that the aggravating degree of rocky desertification in the western region of the study area was higher than that in the eastern region. (5) The dominant factors affecting the evolution of rocky desertification in the past 35 years shifted from natural factor (vegetation coverage) to human activity factor (population density). The research results could provide decision supports for the prevention and control of rocky desertification in Bijie City and even the southwest karst mountainous area.

Landscape fragmentation and structural changes are associated with spatial ecological and social processes. Landscape fragmentation modeling and land use distribution analysis provide a framework within which landscape pattern and structure can be studied and quantified. The Greater Bay Area (GBA) is one of the fastest growing urban agglomeration in China and due to the speedy socioeconomic development and urban expansion, the landscape became more diverse, fragmented, and complex in land use, structure, and shape. This study analyses the spatiotemporal variations in landscape pattern and structure in the Greater Bay Area based on the 40 years’ time-series remote sensing data (1980─2020), fragmentation modeling, and structure change analysis. We used the fragmentation analysis at category and patch level and analyzed the fragmentation over forest, cropland, and grassland. We further employed the economic model of spatial Lorenz Curve and Gini Index for estimating the distribution of land use land cover (LULC) categories and structure changes. The results indicated that the landscape pattern indices of Greater Bay Area as whole, and its eleven cities had an obvious variations and diversity during 1980 to 2020. However, the diffusion and coalescence processes in each city follow distinct patterns. Due to the anthropogenic modifications, the landscape pattern and structural complexity increased gradually during the study period.

Estimating the impact of climate change on energy use across the globe is essential for analysis of both mitigation and adaptation policies. Yet existing empirical estimates are concentrated in Western countries, especially the United States. We use daily data on household electricity consumption to estimate how electricity consumption would change in Shanghai in the context of climate change. For colder days <7 °C, a 1 °C increase in daily temperature reduces electricity consumption by 2.8%. On warm days >25 °C, a 1 °C increase in daily temperatures leads to a 14.5% increase in electricity consumption. As income increases, households’ weather sensitivity remains the same for hotter days in the summer but increases during the winter. We use this estimated behavior in conjunction with a collection of downscaled global climate models (GCMs) to construct a relationship between future annual global mean surface temperature (GMST) changes and annual residential electricity consumption. We find that annual electricity consumption increases by 9.2% per +1 °C in annual GMST. In comparison, annual peak electricity use increases by as much as 36.1% per +1 °C in annual GMST. Although most accurate for Shanghai, our findings could be most credibly extended to the urban areas in the Yangtze River Delta, covering roughly one-fifth of China’s urban population and one-fourth of the gross domestic product.