Water, energy and food are the basic resources for human survival and development. The coordination development of water-energy-food (W-E-F) is of great significance to promote regional sustainable development. In this study, Northwest China (Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang) was selected as the research case, and an evaluation index system was constructed to assess the vulnerability and coordination of water-energy-food (W-E-F) system based on PSR model. Then, a coupled model based on cloud-matter element model and coordination degree model was proposed. The cloud-matter element model was adopted to evaluate the vulnerability level of W-E-F system. The coordination degree model was employed to calculate the coordination degrees of W-E-F system. The results showed that, from 2006 to 2015, the vulnerability levels of W-E-F system in Northwest China were mostly at Level 1. The coordination degrees of W-E-F system belonged to the transitional development level (II) in most years. The vulnerability and coordination problems of W-E-F system in Northwest China were severe. The comprehensive vulnerability index values of W-E-F system were generally on the rise, but far from reaching a good level. Moreover, the comprehensive vulnerability index values and coordination degrees of W-E-F system in Northwest China do not match well. Finally, the countermeasures and suggestions to improve the coordinated development of water resource, energy and food in Northwest China were put forward.2 of 25 scholars and relevant departments. Research on W-E-F system has become an important topic in the field of sustainable development [4].Vulnerability, as an important research object, has been put on the research agenda by international scientific programs and institutions such as IHDP, IPCC, IGBP [5][6][7]. It has become the frontier and hotspot of global environmental change and sustainable scientific research. In 1999, the United Nations Development Programme (UNDP) formally put forward the concept of "economic vulnerability" [8]. After that, the research object of vulnerability has gradually expanded from the natural ecological environment system to the complex system which includes the natural, social, economic and institutional factors. Cutter [9] summarized the related concepts of vulnerability, pointing out that social vulnerability is a natural risk and social response within a specific region or geographical scope, and stressing the imbalance of social preparedness, response, recovery and adaptation to disasters. The United Nations International Strategy for Disaster Reduction (UNISDR) defined vulnerability as the extent to which the attributes of communities, systems or property and the environment are damaged by disaster-causing factors. It was considered that vulnerability was related to various natural, social, economic and environmental factors, and has certain temporal and spatial attributes [10]. Chen et al. [11] indicated that social vulnerability influenced people's ability to make full pre-disaster preparatio...

With the supply of water, energy and food facing severe challenges, there has been an increased recognition of the importance of studying the regional water–energy–food nexus. In this paper, Inner Mongolia, including 12 cities in China, was selected as a research case. A super-efficiency slack based measure (SBM) model that considered the undesirable outputs was adopted to calculate the regional total factor productivity (TFP) and the Malmquist–Luenberger index was used to investigate the change trend of the TFP from 2007 to 2016 based on understanding the water–energy–food nexus. Finally, influential factors of the TFP were explored by Tobit regression. The results show that the 12 Inner Mongolia cities are divided into higher, moderate and lower efficiency zones. The higher efficiency zone includes Ordos, Hohhot, Xing’an, and Tongliao, and the lower efficiency zone includes Chifeng, Xilin Gol, Baynnur, Wuhai and Alxa. There is a serious difference in TFP between Inner Mongolia cities. During the study period, the TFP of the water–energy–food nexus in Inner Mongolia cities shows a rising trend, which is mainly driven by the growth of technical progress change. However, the average ML values of the lower and moderate efficiency zones were inferior to the higher efficiency zone in six of the ten years, so the difference between Inner Mongolia cities is growing. According to the Tobit regression, the mechanization level and degree of opening up have positive effects on the TFP, while enterprise scale and the output of the third industry have negative effects on the TFP. Government support does not have any significant impact on the TFP. Finally, suggestions were put forward to improve the TFP of the water–energy–food nexus in Inner Mongolia cities.

Bacteria constitute great abundances and groups on Earth and control many important processes in terrestrial ecosystems. However, our understanding of the interactions between soil bacteria and environmental factors remains limited, especially in sensitive and fragile ecosystems. In this study, geographic patterns of bacterial diversity across the four sandy grasslands along a 1600 km north-south transect in northern China were characterized by high-throughput 16S rRNA gene sequencing. Then, we analyzed the driving factors behind the patterns in bacterial diversity. The results showed that of the 21 phyla detected, the most abundant were Proteobacteria, Actinobacteria, Acidobacteria and Firmicutes (average relative abundance > 5%). Soil bacterial α diversity, calculated as the bacterial phylotype richness and Faith’s phylogenetic diversity, was highest in the Otingdag Sandy Land and lowest in the Mu Us Sandy Land. Soil EC was the most influential factor driving bacterial α diversity. The bacterial communities differed significantly among the four sandy grasslands, and the bacterial community structure was significantly affected by environmental factors and geographic distance. Of the environmental variables examined, climatic factors (MAT and MAP) and edaphic properties (pH and EC) explained the highest proportion of the variation in bacterial community structure. Biotic factors such as plant species richness and aboveground biomass exhibited weak but significant associations with bacterial α diversity. Our findings revealed the important role of climate and salinity factors in controlling bacterial diversity; understanding these roles is critical for predicting the impacts of climate change and promoting sustainable management strategies for ecosystem services in these sandy lands.