Using data for Chongqing Municipality, China, we conducted a coupling analysis of key indexes to accomplish the following objectives. We aimed to identify a coupling mechanism for the bearing capacity of the ecological environment (BCEE) and the quality of new urbanization based on an examination of the degree of their coupling in Chongqing during the period 2000-2012. We further aimed to evaluate the level of regional coupling and to determine the stage of urbanization at which an optimal outcome could be achieved to ensure sustainable urbanization within the region. Applying an analytic hierarchy process (AHP), we assessed the main indicators of BCEE and the quality of new urbanization in Chongqing. Accordingly, we constructed a model of ecological environment coupling coordination for analyzing the degree of regional coupling between the ecological environment and urbanization quality for evaluating the BCEE of Chongqing's cities and towns in 2000-2012. We obtained the following results for the study period. First, the overall degree of regional coupling of the quality of new urbanization and the BCEE was between 0.967 and 1.000, implying an advanced stage of coupling. Second, the coupling degree ranged between 0.884 and 1.000 in all of the districts and counties of Chongqing, implying a further advanced stage of coupling with a distinct spatial pattern of "one circle and two wings." Third, the coupling degree for all districts and counties matched that of the overall degree of regional coupling, barring obvious spatial variation, especially in relation to BCEE indicators. All of the districts and counties were classified into four types according to the degree of coupling between new urbanization quality and the BCEE. The findings indicate that rapid urbanization has led to increased ecological pressure within the Chongqing metropolitan area because of a concentration of the population within the central city. Moreover, with the fast pace of development in central city districts, their BCEE differs from that of other districts and counties. This will create a pattern of primary urbanization that can lead to an unsustainable situation in the near future. Local governments should, therefore, modify present urban development patterns accordingly. Optimization of resources utilization as well as adjustments in industrial distribution and industrial upgrading are recommended as effective measures that can disperse the population and reduce the pressure exerted by urbanization on the ecological environment.

The soil effective depths are different due to regional features of various types of soils and vegetation, which impacts spatial and temporal distribution of soil moisture storage capacity and land surface water-carbon flux. In this study, the soil effective depth was calibrated using LPJ dynamic vegetation model on the target of remaining watershed water balance in three climate regions (Dongjiang River watershed in humid areas, Huaihe River watershed in humid, semi-humid areas and Jinghe River watershed in semi-humid and semi-arid areas). On this basis, we examined soil moisture storage capacity and land surface water-carbon flux (runoff R, actual evapotranspiration ET and net primary productivity NPP) resulting from variation of the soil effective depth. The results indicated that the estimated soil effective depth is 70 cm in the Dongjiang watershed, 90 cm in the Huaihe watershed and 140 cm in the Jinghe watershed. The soil effective depth and soil moisture storage capacity increase with the increase of drought degree. The correction of the soil effective depth in terms of water balance effectively reduces the simulation error, and affects the simulated results of the land surface water-carbon flux. However, the large or small effect is related to climatic conditions. The annual mean runoff and actual evapotranspiration change significantly in the humid areas, while the NPP changes significantly in the humid and semi-humid areas. The results provide a reference for improving the reliability of application of the LPJ model in different climate regions.

By using the IBIS, a dynamic vegetation model, this study firstly simulated the NPP dynamics of China's potential vegetation in the past 50 years (1961-2010). Then according to the Fifth Assessment Report by IPCC, this study used the average climate conditions during 1986-2005 as the "standard climate", and took the NPP of the potential vegetation in this climate condition as the evaluation basis. Compared with the evaluation basis, the NPP fluctuation of each year was calculated to judge whether the potential vegetation adapts the climate change or not. Meanwhile, the degree of the inadaptability was evaluated. Finally, the NPP vulnerability of potential vegetation was evaluated by synthesizing the times and degrees of inadaptability to the climate change during the past 50 years. Results showed that: the NPP of the desert ecosystems south of the Tianshan Mountains, and the NPP of grassland ecosystems in northern China and western Tibetan Plateau were more likely to be impacted by the climate change in the study period. The NPP vulnerability of these ecosystems to climate change in the past 50 years was relatively high. The NPP of most of the forest ecosystems was not likely to be influenced by climate change. The NPP vulnerability to climate change of the evergreen broadleaved forests and coniferous forests was lower. Additionally, the NPP of the desert ecosystems north of Tianshan Mountains, and the NPP of the grassland ecosystems in the central and eastern parts of the Tibetan Plateau had lower vulnerability to climate change.

Ecosystem services (ES) are the important links between natural ecosystems and human well-being, which draw the attention from many countries and organizations around the world. Traditionally conservationists have focused on conserving biodiversity, mainly through habitat protection, evaluation of endemic or endangered species distribution, and assessment of threats to survival. Recently, conservationists have focused not only on the conservation of biodiversity, but also on the sustainable provision of ES. In this study, a series of composite indicators were used to analyze the spatial-temporal patterns of four types of ES in China from 2000 to 2010. These types of ES include carbon-capture services of vegetation, water provision and purification, soil conservation and habitat protection services of ecosystems. The driving factors and conservation efficiency of the four ES types in the seven conservation and restoration regions of China were assessed based on the results of ES mapping. Finally, the priority levels of ES in China were identified in the study. The main results were as follows: (1) From 2000 to 2010, the spatial scope of four types of ES increased from the northwest to southeast of China. The significantly increased areas of the total ES are mainly distributed on the Loess Plateau while the decreased areas are mainly located in northeastern and northern China ecological regions. The main reasons for the decrease of total ES in northern China are due to the increase of artificial land and loss of cropland. The decreases of total ES in northeastern China are caused by the degradation of forest land and the conversion of forest to cropland or grassland. However, in the Loess Plateau the increases of total ES are caused by the conversion of cropland to grassland or forestland, which led to the significant increase of ES. (2) In the seven conservation and restoration regions of China, all the significant increased area of four ES types is larger than the decreased area from 2000 to 2010. The area proportions of the significantly increased regions of total ES in the Three-North Shelterbelt Project areas are greater than other regions, and the smallest region is the key ecological function area, while the most significantly decreased area is the important ecological function regions, and the smallest significant decreased regions are the Three-North Shelterbelt Project regions. (3) The final scenario of the priority levels of the ES conservational area accounted for 26.18% of China's territory, which protected 64.19% of the total ES values of China and the conservational efficiency is 2.47 times the average level of China.