This study examines landscape changes in the context of China's national Grain for Green (GFG) policy, one of the world's largest "payment for environmental/ecosystem services" (PES) programs. We explored landscape structures and dynamics between 2000 and 2010 in Shaanxi Province, the Chinese province with the greatest amount of cropland conversion and reforestation in recent decades. We used Landsat Thematic Mapper (TM)-derived data and landscape metrics for six land cover classes to determine (1) the major land cover changes during enforcement of the policy, (2) the spatial and temporal variations in these changes, and (3) the effects of land cover changes on landscape structure and dynamics. The results suggested that provincial-level land cover changes modestly reflected the goals of the GFG. Over the 10-year study period, the forest and grassland coverages expanded from 95,737.9 to 97,017.4 km(2) and from 37,235.9 to 40,613.1 km(2), respectively, while the cropland coverage decreased from 59,222.8 to 54,007.6 km(2). The conversion direction differed regionally: the targeted croplands in Shanbei, namely, types III and IV, were mainly transformed into grassland while those in Shannan were mainly transformed into forestland. Reforestation was associated with increased inter-landscape aggregation and connection. Despite this large-scale reforestation trend, we found notable and significant differences in the land cover changes at the subprovincial level.

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As a tool that can effectively support ecosystem management, ecological risk assessment is closely related to the sustainable development of ecosystems and human well-being and has become an active area of research in ecology, geography and other disciplines. Taking Dujiashi Gully for the study of gully loess erosion, a comprehensive risk assessment system for identifying risk probability, sensitivity and impairment was established. The spatial distribution of comprehensive ecological risk was analyzed, the ecological risk management categories were simultaneously delineated based on the risk dominant factor and the risk management strategies were formulated in loess regions. The results were as follows: (1) the spatial differences in comprehensive ecological risk were significantly different in the research area. The regions with extremely high and high risk were mainly located in gully areas and secondary erosion gullies, which are in 28.02% of study area. The extremely low-risk areas covered 1/3 of the study area and were mainly distributed to the northwest and south of the study area, where hills are widely spaced. (2) The combined analysis of ecological risk and terrain found that the elevation decreased first and then rose but the comprehensive ecological risk increased first and then decreased from north to south. Comprehensive ecological risk and terrain generally showed an inverse relationship. (3) The study area was divided into four types of risk management categories. Risk monitoring zones, habitat recovery zones, monitoring and recovery zones and natural regulation zones encompass 14.84%, 12.44%, 26.47% and 46.25% of the study area, respectively. According to four types of risk management categories, different risk reduction measures were designed to improve regional sustainable development capacity. Risk identification and risk management categories based on comprehensive ecological risk model can design a sustainable development path for social ecosystem and local farmers and provide a method for sustainable development for similar gully landscapes.

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As the largest developing country in the world, China's rural areas face many poverty-related issues. It is imperative to assess poverty dynamics in a timely and effective manner in China's rural areas. Therefore, we used the poverty gap index to investigate the poverty dynamics in China's rural areas during 2000-2014 at the national, contiguous poor areas with particular difficulties and county scales. We found that China made significant achievements in poverty alleviation during 2000-2014. At the national scale, the number of impoverished counties decreased by 1428, a reduction of 97.28%. The rural population in impoverished counties decreased by 493.94 million people or 98.76%. Poverty alleviation was closely associated with economic development, especially with industrial development. Among all 15 socioeconomic indicators, the industrial added value had the highest correlation coefficient with the poverty gap index (r =-0.458, p<0.01). Meanwhile, the inequality of income distribution in the out-of-poverty counties has been aggravated. The urban-rural income gap among the out-of-poverty counties increased by 1.67-fold, and the coefficient of variation in rural per-capita income among the out-of-poverty counties also increased by 9.09%. Thus, we argued that special attention should be paid to reducing income inequality for sustainable development in China's rural areas.

W e propose a model where customers are classified into two groups: short lead-time customers who require the product immediately and long lead-time customers to whom the supplier may deliver either immediately or in the next cycle. Unmet orders are backlogged with associated costs. Specifically, the supplier faces two problems: how the onhand inventories should be allocated between the two classes of customers and how the backlogged orders should be cleared when replenishments arrive. We treat the former as an inventory commitment problem and handle the latter with priority rules. We characterize and compare the inventory commitment policies with three priority rules in clearing backlogs. We also explore the optimal inventory replenishment decision and evaluate the performance of each priority rule.