Ecological compensation is a hot subject in academic studies, and the determination of the spatial allocation of compensation payments is a key point in the research of ecological compensation. There are two kinds of thoughts in the determination of regional spatial allocation at present: “evaluation of ecological construction cost” and “evaluation of ecosystem services value”. This paper analyzes the relationships between social ecological compensation and regional socio-economic development, and establishes two econometric models with the data of 2007 from various provinces in China. Through these models, the impacts of geographical endowments on the regional socio-economic development in various provinces are analyzed from the social justice viewpoint and the concept of “equivalent value of geographical endowments” (EGE for short) is proposed. This paper analyzes the application prospect of EGE in the policy making of regional ecological compensation. The results showed that: (1) the implementation of social ecological compensation is not only an effective guarantee for each region to obtain the equal rights of survival, development and decent environment, but also an essential assurance to the coordinated, balanced and sustainable development among various regions; (2) the regional difference in geographical endowments is an important factor affecting the regional spatial variation of socio-economic development. Therefore, geographical endowments are important bases for the determination of the spatial allocation of compensation payments in social ecological compensation; (3) based on the EGE, the government can determine the spatial allocation of social ecological compensation scientifically, and avoid the “sweeping approach” phenomenon in the policy making process of ecological compensation.

The decision tree and the threshold methods have been adopted to delineate boundaries and features of water bodies from LANDSAT images. After a spatial overlay analysis and using a remote sensing technique and the wetland inventory data in Beijing, the water bodies were visually classified into different types of urban wetlands, and data on the urban wetlands of Beijing in 1986, 1991, 1996, 2000, 2002, 2004 and 2007 were obtained. Thirteen driving factors that affect wetland change were selected, and gray correlation analysis was employed to calculate the correlation between each driving factor and the total area of urban wetlands. Then, six major driving factors were selected based on the correlation coefficient, and the contribution rates of these six driving factors to the area change of various urban wetlands were calculated based on canonical correlation analysis. After that, this research analyzed the relationship and mechanism between the main driving factors and various types of wetlands. Five conclusions can be drawn. (1) The total area of surface water bodies in Beijing increased from 1986 to 1996, and gradually decreased from 1996 to 2007. (2) The areas of the river wetlands, water storage areas and pool and culture areas gradually decreased, and its variation tendency is consistent with that of the total area of wetlands. The area of the mining water areas and wastewater treatment plants slightly increased. (3) The six factors of driving forces are the annual rainfall, the evaporation, the quantity of inflow water, the volume of groundwater available, the urbanization rate and the daily average discharge of wastewater are the main factors affecting changes in the wetland areas, and they correlate well with the total area of wetlands. (4) The hydrologic indicators of water resources such as the quantity of inflow water and the volume of groundwater are the most important and direct driving forces that affect the change of the wetland area. These factors have a combined contribution rate of 43.94%. (5) Climate factors such as rainfall and evaporation are external factors that affect the changes in wetland area, and they have a contribution rate of 36.54%. (6) Human activities such as the urbanization rate and the daily average quantity of wastewater are major artificial driving factors. They have an influence rate of 19.52%.

Cultivation is one of the most important human activities affecting the grassland ecosystem besides grazing, but its impacts on soil total organic carbon (C), especially on the liable organic C fractions have not been fully understood yet. In this paper, the role of cropping in soil organic C pool of different fractions was investigated in a meadow steppe region in Inner Mongolia of China, and the relationships between different C fractions were also discussed. The results indicated that the concentrations of different C fractions at steppe and cultivated land all decreased progressively with soil depth. After the conversion from steppe to spring wheat field for 36 years, total organic carbon (TOC) concentration at the 0 to 100 cm soil depth has decreased by 12.3% to 28.2%, and TOC of the surface soil horizon, especially those of 0-30 cm decreased more significantly (p<0.01). The dissolved organic carbon (DOC) and microbial biomass carbon (MBC) at the depth of 0-40 cm were found to have decreased by 66.7% to 77.1% and 36.5% to 42.4%, respectively. In the S.baicalensis steppe, the ratios of soil DOC to TOC varied between 0.52% and 0.60%, and those in the spring wheat field were only in the range of 0.18%-0.20%. The microbial quotients (qMBs) in the spring wheat field, varying from 1.11% to 1.40%, were also lower than those in the S. baicalensis steppe, which were in the range of 1.50%-1.63%. The change of DOC was much more sensitive to cultivation disturbance. Soil TOC, DOC, and MBC were significantly positive correlated with each other in the S. baicalensis steppe, but in the spring wheat field, the correlativity between DOC and TOC and that between DOC and MBC did not reach the significance level of 0.05.

Karamay City is a typical mining city, relying on oilfield exploration and development. After 60 years of construction and development, Karamay has become the first large oilfield and an important base of the national petroleum and petrochemical industry in China. Based on spatial analysis, and Geographic Information Systems (GIS) grid computing and overlay techniques, whilst considering the effect of oilfield development and aimed at the ecological problems of Karamay City in the Xinjiang Uygur Autonomous Region of China, we conducted research on the spatial characteristics of the comprehensive ecological sensitivity of Karamay. The ecological problems of natural environment evolution include soil erosion, land desertification, soil salinization, and biodiversity reduction. The most significant disturbance factor from the activities of humans in this area is oilfield exploitation. This study carries out an analysis of single factor ecological problem sensitivity and integrated ecological sensitivity. The results of the research are as follows: (1) Soil erosion is relatively sensitive, especially in Karamay district, Dushanzi district, north of Urho district and west of Baijiantan district, which is mainly a result of the vertical dropping slopes, serious rainfall erosion and the distribution of scattered woodland. (2) The main types of land desertification are represented by high and moderate grade sensitivities, and high and extremely high sensitive areas are distributed in the intersection of Karamay and Baijiantan districts. This is due to evaporation exceeding rainfall in these areas, and the soil mainly consists of sand and is seldom covered by vegetation. (3) The soil salinizatiion sensitivity grades are mainly moderate, high and extremely high. The highly sensitive areas are mainly distributed in southeast of Baijiantan district, north and east of Karamay district and east of Urho district. The primary causes are evaporation exceeding rainfall and extreme human activities. (4) The main types of biodiversity sensitivity are light and moderate grade. Highly sensitive areas are located in the east and south of Karamay district, north of the Baiyang River basin and parts of the wetland areas. (5) Oil fields development areas are highly ecologically sensitive, which are located in the northern oilfields of Urho district, western oilfields of Baijiantan district, northwestern oilfields of Karamay district and central oilfields of Dushanzi district. (6) The main types of integrated ecological sensitivity are high and moderate. The high and extremely highly sensitive areas are located in the central and northern parts of Karamay district, and southwest of Baijiantan district. The evaluation results will provide guidance for the future planning and development, the protection of the ecological environment and the realization of harmonious social, economic, and ecological development in Karamay City.

Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation’s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression (MSR) models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial autocorrelation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R² from 0.608 to 0.656, but also removed the multicollinearity among independents.

A balanced ecological carrying capacity and its understanding are important to achieve sustainable development for human kind. Here, the concept of ecological carrying capacity has been used for measuring the dependencies between human and nature. China’s ecological balance between supply and demand has become a global concern and is widely debated. In this study the ‘Ecological Footprint’ method was used to analyze the supply- demand balance of China’s ecological carrying capacity. Firstly, the ecological supply and demand balance was calculated and evaluated, and secondly, the ecological carrying capacity index (ECCI) was derived for each county of China in 2007, and finally this paper systematically evaluated the ecological carrying capacity supply-demand balance of China. The results showed that ecological deficit appeared to be the main characteristic of ecological carrying capacity supply-demand balance in 2007 of China at county scale. In general, more than four-fifths of the Chinese population was concentrated in less than one-third of the land area and more than two-thirds of the land area was inhabited by less than one-fifth of the population. The spatial distribution of the ecological carrying capacity demand-supply was unbalanced ranging from significant overloading to affluence from southeastern to northwestern part of China. It appeared to be more dominant in regions located at coastal areas which are attracted by migrants and had a generally higher population density. Along with the rapid development and urbanization trends in China, ecological deficits in these regions will become more severe.

The landscape pattern of Beijing wetlands has undergone a significant change as a result of natural and artificial elements. Supported by remote sensing and GIS technology, using multi-temporal TM images from 1984 to 2008 in Beijing, this paper analyzed the dynamic characteristics of wetlands landscape pattern through selected typical indices including patch area, patch average area, fractal dimension index, diversity, dominance, contagion indices and the spatial centroids of each wetlands type were calculated. Finally, the paper explored the evolution mode and driving factors of wetland landscape pattern. The results were obtained as follows: the total wetland area increased during the period 1984-1996, then decline from 1996 to 2004. The wetland area in 1994 accounted for only 47.37% of that in 2004. The proportion of artificial wetland area was larger than that of natural wetland. The proportion of reservoir wetland was 33.50% to 53.73% and had the maximum average area. pond and paddy field wetland type with the least average area accounted for 16.46% to 45.09% of the total wetland area. The driving forces of the natural river wetland were mainly natural elements; its fractal dimension index was greater than the others. The Shannon diversity index of wetland landscape increased from 1.11 in 1992 to 1.34 in 2004, indicating that the difference between proportions of each wetland type decreased and areas of each wetland type were evenly distributed. The contagion index went down from 65.59 to 58.41, indicating that the connectivity degraded. Miyun Reservoir had the largest area and its area change had a great impact on the location of the centroid. Wetland resources degenerated gradually from the joint effects of natural and artificial factors. During the period 2006-2008, the precipitation increased and the drought condition was relieved. The government implemented series of positive policies to save water resources, and the wetland area increased.

In the urbanizing world, the Yangtze Delta Region (YDR) as one of the most developed regions in China, has drawn a lot of the world’s attention for the remarkable economic development achieved in the past decades. Nevertheless, the rapid economic development was certain to be accompanied by unprecedented consumption and loss of natural resources. Therefore, the analysis of the ecological situation and driving factors of environmental impact was of great significance to serve the local sustainable development decision- making and build a harmonious society. In this paper, the ecological footprint (EF) was taken as the index of the ecological environmental impact. With the help of Geographic Information System (GIS), we studied the spatiotemporal change of ecological footprint at two scales (region and city) and assessed urban sustainable development ability in YDR. Then we discussed the driving factors that affected the change of ecological footprint by the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The results showed that increasing trends of regional ecological footprint during 1998-2008 (1.70-2.53 ha/cap) were accompanied by decreasing ecological capacity (0.31-0.25 ha/cap) but expanding ecological deficit (1.39-2.28 ha/cap). The distribution pattern of ecological footprint and the degree of sustainable development varied distinctly from city to city in YDR. In 2008, the highest values of ecological footprint (3.85 ha/cap) and the lowest one of sustainable development index (SDI=1) in YDR were both presented in Shanghai. GDP per capita (A) was the most dominant driving force of EF and the classical EKC hypothesis did not exist between A and EF in 1998-2008. Consequently, increasing in ecological supply and reducing in human demand due to technological advances or other factors were one of the most effective ways to promote sustainable development in YDR. Moreover, importance should be attached to change our definition and measurement of prosperity and success.