Global closed basins, occupying almost one fifth of the world’s land area, spatially coincide with arid and semiarid areas. Paleoclimatic proxies can indicate basin-wide environmental change and human activity. However, previous studies have not approached the use of proxies in the same way to reconstruct natural and anthropogenic processes at regional and global scales. Here we present a regional study to investigate the basic processes of paleoclimatic proxies, from a typical closed-basin system in arid China. We use multiple paleoclimatic proxies of surface samples and sediments, as well as groundwater and sediment ages to study environmental change and human activity. We then establish a dataset for paleoclimatic proxies from global closed basins and do a numerical analysis on it. Regional studies verify that human activity greatly impacts paleoclimatic proxies, especially with regard to surface samples, as well as groundwater age, but Holocene sediments are less affected. Results from global studies indicate that the major changing trend of the wet/dry status of closed basins is associated with the movement of the westerly jet streams controlled by long-term changes in winter insolation. There is an abrupt change between 1800 AD and 1900 AD, according to a numerical synthesis of paleoclimatic proxies from global closed basins, which can be linked to human impact. We suggest this time period can be considered as a start point for the Anthropocene based on the sedimentary evidence of closed basins, globally.
The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May (spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3-7 months, responding weakly to hydrothermal dynamics on a scale of 11-12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200-3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.
The red beds in Zhejiang province of China host the highest concentration of Danxia arched rock shelters in the world, just as the Colorado Plateau in the western USA hosts the world’s largest concentration of natural arches and bridges. This study investigated the geological background of the arched rock shelters and compared them to the natural arches and bridges, based on field study and a literature review. It was found that Zhejiang arched rock shelters differ from Colorado Plateau natural arches and bridges in geometry and formation mechanism. Statistical geometric data on arch geometry shows that Danxia arched rock shelters in Zhejiang tend to be relatively flat. They are relatively low features with long spans, and great depth. The natural arches and bridges on the Colorado Plateau are similar to each other, but the bridges are larger than the arches. The geometric differences between the arched landforms could be attributed to their different geologic history and to their different formation mechanisms. The arched rock shelters in Zhejiang are formed by differential weathering between sandstone and conglomerate due to moisture-induced tensile stresses. In contrast, natural arches on the Colorado Plateau are closely related to the Salt Valley anticline, vertical tectonic fractures, and horizontal discontinuities in rock fins. The Colorado Plateau natural bridges were formed by river erosion.
In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors, the urban surface temperature patterns of Changsha in 2000, 2009 and 2016 are retrieved based on multi-source spatial data (Landsat 5 and Landsat 8 satellite image data, POI spatial big data, digital elevation model, etc.), and 12 natural and human factors closely related to urban thermal environment are quickly obtained. The standard deviation ellipse and spatial principal component analysis (PCA) methods are used to analyze the effect of urban human residential thermal environment and its influencing factors. The results showed that the heat island area increased by 547 km2 and the maximum surface temperature difference reached 10.1℃ during the period 2000-2016. The spatial distribution of urban heat island was mainly concentrated in urban built-up areas, such as industrial and commercial agglomerations and densely populated urban centers. The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs. There were multiple high-temperature centers, such as Wuyi square business circle, Xingsha economic and technological development zone in Changsha County, Wangcheng industrial zone, Yuelu industrial agglomeration, and Tianxin industrial zone. From 2000 to 2016, the main axis of spatial development of heat island remained in the northeast-southwest direction. The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9° in 2000-2009. The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9° in 2009-2016. On the whole, the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity. Through the PCA method, it was concluded that landscape pattern, urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha. The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors. The temperature would rise by 0.293℃ under the synthetic effect of human and natural factors. Due to the complexity of factors influencing the urban thermal environment of human settlements, the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment, deepen the understanding of the causes of urban heat island effect, and clarify the correlation between human and natural factors, so as to provide scientific supports for the improvement of the quality of urban human settlements.
Promoting regional coordinated development strategy is one of the important strategies in the new period of China. Faced with the reality of unbalanced and insufficient regional development in China, it is objectively necessary to construct one or more main axes supporting the coordinated and balanced development of regions to become the identification line representing the pattern of coordinated regional development. The results show that the Bo-Tai line, the northwest-southeast axis connecting Bole of Xinjiang and Taipei of Taiwan, can be built into national development backbone line and regional balanced development line, just perpendicular to Hu Line. In 2016, the area of southwest half and northeast half of Bo-Tai Line accounts for 60%: 40%, while the population accounts for 45%: 55%, the economic aggregate accounts for 40%: 60%, the per capita GDP ratio accounts for 44%: 56%, the population density ratio accounts for 38%: 62%, the economic density ratio accounts for 32%: 68%, and the urbanization level ratio accounts for 48%: 52%. The main average indicators are gradually tending to balanced development pattern. Further analysis shows that Bo-Tai Line is a strategic shoulder pole connecting two core zones of “the Belt and Road”, and is the peaceful reunification line of China’s national tranquility and Taiwan’s return. Bo-Tai Line is also a solid line supported and connected by comprehensive transportation channels and a Pipa type symmetrical line for the development of cities and urban agglomerations. It is the backbone of the two-way opening up and the linkage development line between land and sea. It is also an important dividing line that promotes the coordinated development of the eastern, central and western regions, and addresses the imbalance and inadequacy of regional development. Bo-Tai Line plays an irreplaceable strategic role in promoting the coordinated and balanced regional development. It is suggested that the construction of Bo-Tai Line should be included in the national development strategy, and the development strategic plan of Bo-Tai Line should be formulated to fully release the multiple potential functions. We should build three strategic support points: the northwest endpoint, the central strategic node and the southeast endpoint; carry out a comprehensive scientific investigation of the Bo-Tai Line, and strengthen the scientific cognition and publicity; promote China’s development in a higher- level, higher-quality, more coordinated, safer and more civilized direction. Let Chinese know about the Bo-Tai Line, let the world know about the Bo-Tai Line, and let the Bo-Tai Line truly become the backbone of the great rejuvenation of the Chinese nation.
The theory on the cyclic adaptation between society and ecosystems sheds new light on the evolution and internal structure of human-environment systems. This paper introduces the risk index (RI) and adaptation capacity index (ACI) to evaluate the rural human-environment system. An evaluation index system for the adaptability of rural human-environment systems is configured in the context of climate change and policy implementation. On this basis, the stages, features, dominant control factors, and evolution mechanism were examined vis-à-vis the adaptability of the rural human-environment system in Darhan Muminggan Joint Banner from 1952 to 2017. The main results are as follows: (1) The evolution of the rural human-environment system can be divided into three stages, namely, the reorganization and rapid development stage (1952-2002) with population, cultivated land, livestock and degraded grassland increasing by 260%, 13%, 134% and 16.33%, respectively. The rapid to stable development stage (2003-2010) with population increasing by 2.8%; cultivated land, livestock and degraded grassland decreasing by 2.3%, 13.6% and 10.7%, respectively. The stable to release stage (2011-2017) with population, cultivated land, livestock and degraded grassland decreasing by 2.6%, 0.2%, 10.6% and 3.8%, respectively. (2) With the passage of time, the ACI of the rural human-environment system first increased slightly (-0.016-0.031), followed by a slight decline (0.031-0.003), and culminating in a rapid increase (0.003-0.088). In terms of spatial patterns, adaptability is high in the middle, moderate in the north, and low in the south. (3) The evolution of adaptability in the rural human-environment system was mainly controlled by the per capita effective irrigation area (22.31%) and the per capita number of livestock (23.47%) from 1990 to 2000, the desertified area (25.06%) and the land use intensity (21.27%) from 2000 to 2005, and the per capita income of farmers and herdsmen (20.08%) and the per capita number of livestock (18.52%) from 2010 to 2007. (4) Under the effects of climate change and policy interventions, the cyclic adaptation of the rural human-environment system was propelled by the interactions between two kinds of subjects: farmers and herdsmen on the one hand and rural communities on the other hand. The interaction affects the adaptive behavior of the two kinds of subjects, which in turn drives the cyclic evolution of the system. As a result, the system structure and functions developed alternatively between coordinated and uncoordinated states. Small-scale adaptive behaviors of farmers and herdsmen have a profound impact on the evolution of the rural human-environment system.
As the main form of new urbanization in China, urban agglomerations are an important platform to support national economic growth, promote coordinated regional development, and participate in international competition and cooperation. However, they have become core areas for air pollution. This study used PM2.5 data from NASA atmospheric remote sensing image inversion from 2000 to 2015 and spatial analysis including a spatial Durbin model to reveal the spatio-temporal evolution characteristics and main factors controlling PM2.5 in China’s urban agglomerations. The main conclusions are as follows: (1) From 2000 to 2015, the PM2.5 concentrations of China’s urban agglomerations showed a growing trend with some volatility. In 2007, there was an inflection point. The number of low-concentration cities decreased, while the number of high-concentration cities increased. (2) The concentrations of PM2.5 in urban agglomerations were high in the west and low in the east, with the “Hu Line” as the boundary. The spatial differences were significant and increasing. The concentration of PM 2.5 grew faster in urban agglomerations in the eastern and northeastern regions. (3) The urban agglomeration of PM2.5 had significant spatial concentrations. The hot spots were concentrated to the east of the Hu Line, and the number of hot-spot cities continued to rise. The cold spots were concentrated to the west of the Hu Line, and the number of cold-spot cities continued to decline. (4) There was a significant spatial spillover effect of PM2.5 pollution among cities within urban agglomerations. The main factors controlling PM2.5 pollution in different urban agglomerations had significant differences. Industrialization and energy consumption had a significant positive impact on PM2.5 pollution. Foreign direct investment had a significant negative impact on PM2.5 pollution in the southeast coastal and border urban agglomerations. Population density had a significant positive impact on PM2.5 pollution in a particular region, but this had the opposite effect in neighboring areas. Urbanization rate had a negative impact on PM2.5 pollution in national-level urban agglomerations, but this had the opposite effect in regional and local urban agglomerations. A high degree of industrial structure had a significant negative impact on PM2.5 pollution in a region, but this had an opposite effect in neighboring regions. Technical support level had a significant impact on PM2.5 pollution, but there were lag effects and rebound effects.
Payments for Ecosystem Services (PES) programs have been implemented in both developing and developed countries to conserve ecosystems and the vital services they provide. These programs also often seek to maintain or improve the economic wellbeing of the populations living in the corresponding (usually rural) areas. Previous studies suggest that PES policy design, presence or absence of concurrent PES programs, and a variety of socioeconomic and demographic factors can influence decisions of households to participate or not in the PES program. However, neighborhood impacts on household participation in PES have rarely been addressed. This study explores potential neighborhood effects on villagers’ enrollment in the Grain-to-Green Program (GTGP), one of the largest PES programs in the world, using data from China’s Fanjingshan National Nature Reserve. We utilize a fixed effects logistic regression model in combination with the eigenvector spatial filtering (ESF) method to explore whether neighborhood size affects household enrollment in GTGP. By comparing the results with and without ESF, we find that the ESF method can help account for spatial autocorrelation properly and reveal neighborhood impacts that are otherwise hidden, including the effects of area of forest enrolled in a concurrent PES program, gender and household size. The method can thus uncover mechanisms previously undetected due to not taking into account neighborhood impacts and thus provides an additional way to account for neighborhood impacts in PES programs and other studies.
